RFinance Talk Market Efficiency.ipynb

{
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   "source": [
    "# Is it Real? Or is it Random?\n",
    "\n",
    "#### A Financial Turing Test of the JSE using the [emh R Package](https://github.com/StuartGordonReid/emh)"
   ]
  },
  {
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   },
   "source": [
    "An R/Finance talk by Stuart Reid, Chief Engineer [@NMRQL](http://www.nmrql.com) and Blogger [@TuringFinance](http://www.turingfinance.com)"
   ]
  },
  {
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   },
   "source": [
    "# BACKGROUND INFORMATION"
   ]
  },
  {
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   "outputs": [],
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   "source": [
    "There is a legend that Professor Burton G. Malkiel, author of [_A Random Walk Down Wall Street_](https://www.amazon.com/Random-Walk-Down-Wall-Street/dp/0393330338), constructed a price chart by flipping a coin and presented it to a world-renowned chartist to analyze. The chartist studied the movements of the fictitious security and exclaimed that it was a textbook pattern and a once-in-a-lifetime opportunity ..."
   ]
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  {
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   "source": [
    "### Can you guess which one is the \"coin\"?\n",
    "\n",
    "One line is a jump diffusion process and the other is an asset taken from the JSE Top 40 over a random one-year period\n",
    "\n",
    "![A Financial Turing Test](http://www.turingfinance.com/wp-content/uploads/2016/11/RealOrRandom2.png \"A Financial Turing Test\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## The Random Walk Hypothesis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "fragment"
    }
   },
   "source": [
    "The [Random Walk Hypothesis](https://en.wikipedia.org/wiki/Random_walk_hypothesis) is a 116-year-old _empirical assumption_ that security prices can be modelled by a random walk, a stochastic process.\n",
    "\n",
    "The Random Walk Hypothesis is not an economic theory nor is it even an assertion that markets are _literally_ random. It is merely an assumption."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "And it is an assumption which lies at the heart of everything we quants hold dear: **risk metrics**, **derivatives**, **mean variance optimization**, even **sharpe ratios!**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "It was only in the 1970's that the _empirical assumption_ of randomness was finally justified by an _economic theory_ called the [Efficient Market Hypothesis](https://en.wikipedia.org/wiki/Efficient-market_hypothesis). \n",
    "\n",
    "The Nobel-prize worthy Efficient Market Hypothesis explained the Random Walk Assumption using the counter-intuitive lexicon of [Classical Information Theory](https://en.wikipedia.org/wiki/Information_theory)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "## Classical Information Theory"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "fragment"
    }
   },
   "source": [
    "Consider the following two binary strings,\n",
    "\n",
    "* \"1111111111111111111111111111111111111...\"\n",
    "* \"1101000101001000100010000100110100110...\"\n",
    "\n",
    "Which string contains more information? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "fragment"
    }
   },
   "source": [
    "The first string contains almost no information because all of the bits are exactly the same ad infinitum. Knowing one bit is sufficient to know what every other bit will be. \n",
    "\n",
    "The first string is called _determinstic_, _predictable_, or simply just _boring_."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The second string contains lots of information because knowing one bit does not seem to be sufficient to know what any other bit will most likely be. \n",
    "\n",
    "The second string is called _stochastic_, _unpredictable_, or simply just _interesting_."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## The Efficient Market Hypothesis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The Efficient Market Hypothesis argues that investors trading on new information reflect that informaton into the price of the security thereby making it more random; the Efficient Market Hypothesis is a byproduct of participation by many _intelligent_ agents."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "fragment"
    }
   },
   "source": [
    "The Efficient Market Hypothesis is an _Economic Theory_ because it allows for investors to be reimbursed for taking on risk when they invest in the market. This return, called the market risk premium, is the expected rate of return of a diversified portfolio. This premium explains why buy-and-hold investors and index funds have a non-zero expected return!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "fragment"
    }
   },
   "source": [
    "So when proponents of the Efficient Market Hypothesis say _\"active investors can't beat the market\"_ what they really meant to say is that _\"active investors can't generate returns above the market risk premium with less risk than the market (a.k.a abnormal returns)\"_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## The Three Forms of EMH"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The Efficient Market Hypothesis distinguishes between three forms of market efficiency: weak-form, semi-strong-form, and strong-form. These differ according to the set of information, $\\Phi$, which is reflected by investors into the price of securities,"
   ]
  },
  {
   "cell_type": "markdown",
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   },
   "source": [
    "* $\\Phi_{weak} = \\{\\textrm{Historical Price Data}\\}$\n",
    "* $\\Phi_{semi-strong} = \\{\\textrm{All Public Information}\\}$\n",
    "* $\\Phi_{strong} = \\{\\textrm{All Information incl. Non-Public}\\}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Random Walk Hypothesis typically deals with just the first form of market efficiency, but theoretically it could be used to test the hypothesis that the market is efficient with respect to any subset of information, $\\Phi_i$. More on that later ..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Getting to Martingales from EMH"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "If the current price of a security reflects all historical price data, then the expected price of the security tomorrow _with respect to_ historical price data is its price today,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$E[S_{t+1}|\\Phi_{weak}] = S_{t}$ or alternatively,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Let $r = ln\\Big(\\frac{S_{t+1}}{S_{t}}\\Big)$ then,\n",
    "\n",
    "$E[r_{t+1}|\\Phi_{weak}] = ln\\Big(\\frac{E[S_{t+1}]}{S_{t}}\\Big) = ln(S_{t}/S_{t}) = ln(1) = 0$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The above model is called a Martingale and it is the purest type of random walk! But, it does not reflect the equity risk premium ..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Getting to Submartingales from EMH"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "If the current price of a security reflects all historical price data, then the expected price of the security tomorrow _with respect to_ historical price data is greater than today's price because securities are _risky_ assets and we should be rewarded for taking on that risk,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$E[S_{t+1}|\\Phi_{weak}] \\geq S_{t}$ or alternatively,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$E[r_{t+1}|\\Phi_{weak}] \\geq  0$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "This is called a Submartingale random walk and it is the underlying assumption of most quantitative models. The Submartingale Random Walk Hypothesis is a _consequent_ of the Efficient Market Hypothesis which is the _consequent_ of active investment,\n",
    "\n",
    "$\\textbf{Intelligent Investors} \\rightarrow \\textbf{Efficient Market} \\rightarrow \\textbf{Random Walks}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## A Comment on Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "One, often overlooked, aspect of market efficiency is the set of models, $\\mathcal{M}$, used by investors. Consider that \"random string\" we looked at earlier, \"1101000101001000100010000100110100110\", and now consider the below model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] 112358132134\n"
     ]
    }
   ],
   "source": [
    "model <- function(binstr) {\n",
    "    sum(2^(which(rev(unlist(strsplit(as.character(binstr), \"\")) == 1))-1))\n",
    "}\n",
    "print(model(\"1101000101001000100010000100110100110\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Does it look familiar? 1, 1, 2, 3, 5, 8, 13, 21, 34, ... The sequence may look random to our mental model in binary, but to our model above it is decidedly **not random**! Therefore models are an important aspect of market efficiency,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Quantitative investing is the belief that with respect to any set of information, $\\Phi_{i}$, and some set of models, $\\mathcal{M}$, security prices consist of a _signal component_ and a _noise component_. So for some combinations of $\\Phi_{i}$ and $\\mathcal{M}$ the market may be totally random, but for some other combinations of $\\Phi_{i}$ and $\\mathcal{M}$ is may only be semi-random. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Quantitative investors try to find combinations of $\\Phi_{i}$ and $\\mathcal{M}$ that reduce the randomness of the security we are trading. We seek information-rich data and build powerful models."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# RANDOMNESS TESTING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
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    }
   },
   "source": [
    "## What Distribution?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "If the markets are random walks, what type of distribution to they have? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Generally speaking you get two types of randomness tests: parametric and nonparametric. \n",
    "\n",
    "* Parametric tests assume something about the underlying distribution \n",
    "* Nonparametric tests don't assume anything about the underlying distribution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "A good test of the random walk hypothesis makes few assumptions about the data ... but may, as a result, be less powerful than another more specific test. \n",
    "\n",
    "This, and biases in randomness tests, are the reason why I believe we should ensemble randomness tests together when testing the random walk hypothesis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## What Frequency?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "And if the markets are random walks, are they random in all frequencies?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Most statistical tests of randomness are conducted on returns computed over a specific period of time, usually daily. But just because daily returns are random doesn't automatically imply that weekly or monthly returns are random too."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "As such most randomness tests are conducted in multiple frequencies or rather, across multiple lags. Eugene Fama's original paper looked at lags from one to ten days. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "All of these issues are what inspired me to write the emh package for R. This package, which we will be going through shortly, makes it increadibly easy to run a suite of randomness tests on a financial time series object and extract the results of each test in the suite on the data sampled at different frequencies."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# THE RANDOMNESS TESTS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "library(emh)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## The Five Types of Randomness Tests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "fragment"
    }
   },
   "source": [
    "For weak-form market efficiency testing there are five types of randomness tests,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "1. Runs - the number of runs or the length of the longest (+) or (-) run\n",
    "2. Serial correlation - non-zero correlation between an asset and itself\n",
    "3. Unit roots - the presence of reversion to the trend line after shocks\n",
    "4. Variance ratios - higher or lower variances at _specific frequencies_\n",
    "5. Complexity tests - non-computability or compressibility in markets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "These are all univariate tests done to determine whether a time series of returns, $r$, is random with respect to itself, $\\Phi = r$. Multivariate tests do exist but have, unfortunately, not been applied very often in the context of market efficiency testing ..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## [The Runs Test](https://en.wikipedia.org/wiki/Wald%E2%80%93Wolfowitz_runs_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "A run is a continuous sequence of either (-)'s - down days - or (+)'s - up days. In the early 1940's Abraham Wald and Jacob Wolfowitz proved that the distribution of the _number of runs_ is for large sample sizes is approximately normally distributed with,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$\\mu = \\frac{2 N_{+} N_{-}}{N} - 1$ and\n",
    "\n",
    "$\\sigma^2 = \\frac{N_{+} N_{-}(2 N_{+} N_{-} - N)}{N^2 (N-1)} = \\frac{(\\mu - 1)(\\mu - 2)}{N - 1}$\n",
    "\n",
    "where $N_{+}$ is the number of number of +'s and $N_{-}$ is the number of -'s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "This test if _nonparametric_ meaning that you can have 90% of your day's being (+) and still test whether or not the sequence was random. This is quite a simple test which was used by Fama in his original papers on market randomness."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## [The Durbin-Waton Test](https://en.wikipedia.org/wiki/Durbin%E2%80%93Watson_statistic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The Durbin-Watson test is named after James Durbin and Geoffrey Watson. It is a test for statistically significant levels of serial correlation in a time series. The Durbin-Watson is conducted on the residuals, $\\epsilon$, from a regression analysis on the returns with itself. \n",
    "\n",
    "As such, the test does take into account drift ... but only if you assume that drift is stationary and constant. The test can be done on the residuals of a moving average,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$d = \\frac{\\sum^{\\tau}_{t=2}(\\epsilon_{t} - \\epsilon_{t-1})^2}{\\sum^{\\tau}_{t=1} \\epsilon_{t}^2}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "James Durbin and Geoffrey Watson proved that the distribution of the test statistic $d$ is _asymptotically_ distributed according to the Chi-Squared distribution for random walks. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## [The Ljung-Box Test](https://en.wikipedia.org/wiki/Ljung%E2%80%93Box_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The Ljung-Box Test is named after Greta Ljung and George Box. The Ljung-Box test is a test of whether any autocorrelation, $\\rho_i$, in a group of autocorrelations computed at lags 1 to $h$ for a time series are significantly different from zero,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$Q = \\tau(\\tau + 2)\\sum^{h}_{k=1}\\frac{\\hat{\\rho}^{2}_{k}}{\\tau - k}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "where $\\tau$ is the length of the time series and $\\hat{\\rho}^{2}_{k}$ is the squared autocorrelation calculated with lag equal to $k$. Greta Ljung and George Box proved that the test statistic, $Q$, is asymptotically distributed according to the Chi-Squared distribution."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## [The Breusch-Godfrey Test](https://en.wikipedia.org/wiki/Breusch%E2%80%93Godfrey_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The Durbin-Watson Test and the Ljung-Box Test are used very often, however some studies indicate that they are biased toward the null hypothesis. In other words, they are more likely to say that a time series is random than non-random."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The Breusch-Godfrey Test was developed by Trevor S. Breusch and Leslie G. Godfrey and is considered a more powerful test for autocorrelations than either the Durbin-Watson or the Ljung-Box test. The Breusch-Godfrey test also tests for statistically significant autocorrelation in the residuals, $\\epsilon$, from a regression analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Breusch and Godfrey proved that if you fit an auxiliary regression to the original data and the lagged residuals from a linear regression the statistic, $n R^{2}$, is asymptotically distributed according to the Chi-Squared distribution,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Variances at Different Frequencies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Some of the most powerful randomness tests which exist are called Variance Ratio tests. In a random walk process the variance should scale linearly in the sampling interval."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "We can express this relationship as the ratio of variances at two different frequencies,\n",
    "\n",
    "$\\sigma^2_{f=1} \\approx n \\sigma^2_{f=n}$ ... therefore,\n",
    "\n",
    "$\\frac{\\sigma^2_{f=1}}{n \\sigma^2_{f=n}} \\approx 1$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "However if there are patterns or cycles in the returns data then the variances will not scale linearly in the sampling interval and the variance ratios will be off."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Xn3aMDLj7Gu9aOPaNrO6ZO7U0j+1p36gb4qLUlIjjgg/f1v2N/dEo+kDkxKSzIk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\nHFCQCOGAgkQIBxQkQjj4P2krsiJ/1eGhAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's simulate a simple GBM random walk.\n",
    "dates <- seq.Date(Sys.Date(), Sys.Date() + 2520, 1)\n",
    "gbm_walk <- emh::simulate_brownian_motion(n = 2520)\n",
    "gbm_walk <- zoo::zoo(gbm_walk, dates)\n",
    "plot(emh::as_levels(gbm_walk))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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cnT6AFz+X3oXr2DBDoe/g5sxeaay9RTB9rBN7iKUGCL/8BcJvvkQSGcxlWEAlsr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\nolxZUW+D73aHoBB8IWU5rN+LTgjX5VQzf3rjrXX8ggQvBV9IRvz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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now let's print it's variance at different frequencies.\n",
    "variances <- c()\n",
    "for(i in 1:55) {\n",
    "    suppressWarnings(variances <- c(variances,\n",
    "                                    var(emh::as_frequency(gbm_walk, i)))) \n",
    "}\n",
    "plot(variances)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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R5E6Htl7YCQlTf3YimksOSSchNE6I3mtmFAVXVxsSaXVqe1vXngSgQ8ZH5JijTI\n73l7sdzKv+jygaVpr/X0fXBfyGdwgLE1U7GUO0QCFVNUH8fYPhSLo7XiT6iJ2qbQWj66WtQS\nPKyslH7aa6YxKaSw5CIWJrhYIu/AOm1tqSaXwpHcNnPtr+oPrwsPZH5JklTL63l7UUoFEFUC\nJwMprPJTd9CEFgZRW63J//AW448glImoPJo6QXF81mB7XzV16FTeXaLnN/0iHVVW5i/D614K\nl0IKS85jzj0Xu69PuU8nZ6WmlSzCEqbkLO5A68amBwtNahw5zUrl9ryrMKUCiCjo6t7qizK9\n/wWfNOqPvcrDrgoWsfT8WhRH+ZGO8W182l/tQE6ntQnLEQ/Kc3hCWVm4EtO8FC6FFJacwdQ7\nLrPsO+Fwq1mtaSVOdCGKvqa2YFx4N+R1DphHhrB8XpLQFMzC2H3kdHVv9UWRJ66Du6j3o7Tv\ndcthPuNtORRCyREO0wXsHEw6U5hFa6/vQ1ZcVdZ+U1YWr4a3oIBSSGHJabxyCxjv3HDOORS+\nVtNKStGFKDj+UuYHhfROyOscMC37sxxektDkz0S5bDK5urf6Im/PK6hNC32xm7GaJTGXpebX\nIi8KD3VYpeKLZ7GfH8+DN8zYjzz8R+qcsrJkrT6gugtSSGHJrxh709tQ7EanWvq+qaznq549\no2NLtnrqwsrQVjgxNO3DsnnJnZEvA82lpcUPgZSXtfvf4J61T5KpQvXCeIOJocycyDuIEg0I\nvhrBR+kYW0Rrsw6gcEpa+0tZWfYuZnspXAopLDmGl67DS8f3Q6eQypIRUa7CqUVXgAbrmpxS\ndy0JaX0TRaNeLIuaO+PGBdddeeJpLi2lesf7Sfzjf4IPbfbCLsYq51NEEcWvRRZkf5riowu+\nHqnOVi+jtTkHUS49rf1Dvz6bFPF5RgopLDmCkVfhpZmxwymkQt2V9ew5UqYTq5Xzo/lpdddC\n5Se4zL8eC0gq1OvGMmUQiy83d92VK61I5b4/kPLSdDkHPmvdg8a3K+TATDWvVHpk7MPYe+qV\n+eYlPtzNMxwCcw/jBS5XytO7ajNkorFkxWE81xxevtRdzrnX7OQtkSWd8KoAxmzEQ7+ru96k\nUak/L8T/FdqKB0KtLix9vFh8obbLnv3ZUzNGfiF1AgktlqrTGXDL3scpx3uZzJimZjpMg7S9\nKKyzYN/L6mAg3zD/J9VO9Y7yQH9nq1e5SCGFJd/zVIyLPO7bq+XGAuLIbjVDCqge1OPfR+uz\n6q5Z5Cj6x9HAZmJCS/WOLJ1qBfdcdf2OGxGIYYz8QnJ19XSiF6I6nkYZ9urz7DEyXSiZDlNv\ni2sRjVTdKP6q4LtXVIveTfzJfVQzr4uIx9ptWOClcCmksGQ//8qXedx3EPW1gEGRZCWUztHS\ne3Uz2p5Xl5X+1Wv47VBgMzGhpUpbljaNWBzuEqPhonLvM/an8inStfd0omcS0P5XlGS927PO\n2HKfFY3FlJta3zGii3P+7ftJwu9PdDbfOoYp4vyU+bD+Uy8/XlJIYYqwoFzlcd8RTNZGctFS\nWU/tENJrW9HxL3V5Mnlc//ptYDMxoaVCK5ZajXE/1MUjVmmeRtGktPLS0v/i7uKRX1CM9WrN\nHkXsTFYwCpOuOi5NR6dFyKGpOMdP4Fdx2XFtDjZtRWz8HIu9lB56Id04/U+Cr2OkkHywm3/l\n6zzu+xVTj2j3B1nEOK1Vp3+MzpfV5Qnsi674ZXdgMzGhpUwLliqVWHymmH7HMR7BkTdSG3o6\n0TP/ovURFGLdW7L2wMtH8gATLzsuTVt1tFvh8HTVqHwnDXOu/lUb09k9Eu9/6XW0M7RC+qRb\n0XilqqkLDzlkeJwUkg+4OUvkRx73ncW0X7T7g1LTRTnultk70FWLgTKWQrIe2RnYTExoKdGE\npUwpFgcV0G3fOgIUU5hMDfA/j2d65BoePoTs+7o2oYhlw8k9YvxfjkvTbCebpy4emQ3hBfUV\neexvOEUDnJwJ2PI1VngtPXRCSugNxFdq3LZx5YxAz3sGR0oh+WAnfeO7PT/ZL2Ppr9r9UcsZ\nGUdh7qfornYL8BKlrfhhW2AzMaGlaNk6kZFicUAu3faOZDp4lZ2ijxFAfLsraPkdkK1LfUpX\nzgM7j1nuuDSpI+/NURd/fpObBFH7OQ3w4W8OI5BX8dE+SmrtkVAKaSaqfC4swu7taeTVQ4qQ\nQvIBjw11wsvOb+//pt0f1ahr4GDh5+ilxYkcSan9DmzGdyGtd0AUJF9EsdhPb+FQkRqrafaQ\nFSlK+F/cX2hOXcuWtdnDQJTCsnMAACAASURBVFU6uRF0/DtTXfh1AW7yE75HeuCTM9iiFjAF\n275zrLgTSiFVy+WcALxbvrDBkVJIPuD94JNed2tj3PSDfct5r7y1C320B9RzrBywbwP2ha7S\ngZI3BiItBGN90+u2C4fw+TzAQiH/izuPJtS1rFCdtQTK0clZ9EK69rq68PtiNevLrQWFgS//\nwBdqAa/jk4Oqz9+DhFJIcfqxysHRXo+TQvLJNvrGT3vd7YgYVIax6857ZflXeFoLJtpwRVHg\n63ewJ4S1DpCcNIovmjC99cFhS/APwCPKwovjnyfOoNEXyhmlKlPvkJfhHM9UuDRFXTi/DFqb\nuZjyW3PB0fqdgZ2Hvbroh1JINXI7n0j3Khr9lkgh+YAHov7d625HJ7q4GCVWWbUHA1m0ulI1\nL7BrOZJwzFXu/MHj733bM4Vue1HxG8H/e3H888RpNKAWcZFylEKK8uDAOQyjcOFVTVErI7VT\nFLkduj9bCwE4B7uO4KCX0q0Q0r9n/bPZmuPsI33TyGs4FkIKyQfcUtl7wAJHVNWCKzdmdd4r\na/diCItVV0orDZudix3tliQId1+lW+tmRIkI3fZCQkL8vxfHP0+cQD36/clbijXicZTcOMtj\nnSAFrr3jaCyViuKBu1TmYfcv+nUXTAopYd+4emRanL7eON+N7YSngPjKTdo1rZoRePyuwZFS\nSD7gk+7nvO52xPmOwMuRzntlw34MU33ZFI2lBXYsIKuzpArNlPCsyFeUXr9ue35ef2HR7sXx\nzxM/o/YW5YzsRVkDt+4R55TIgBSHW+sd7ciymVPqzM4XYc+lSle8lG5KSPdWVEZU+U79R/bv\nVD4KVVYajWhzfnq6iPL1IbbQYONRVykkH2zhjRGvu52ZJ6CLBI8PDuB51bsayKD0QD6ai09C\nWOsAoVsF15hoqep+d0UoF9Eu8+L454kfUZlCEmcsQAP/Drspx+/Mul78JSsS3ovXTilf/h9d\nAUuNRmbMCOm7ymm7b9OSCF7f1iNtlQN+nH3tlLRsMM1m+s69B3WjMe4okTNWy8ZNfHwIo5je\nW3bzG0k5mhD/AHQnk3NqRqfHhD7UZVb/izskAjmnzcNq84BkgjTagmrpmzcF++c97ZSKlfQF\nrDSaKzAjpKyTr7tsvz4pgI9liBSSD96n7/yS9/3KLZNDdI566+66zw5jDMuua+u9NwtbQ1fp\nQEmpfUju+vGxY7s+AkVm/4v7TpwRnZ0ygTougqONl128FIvVnVK5qr6Ad7yONDBzQvrHZWvC\nA1sSjxSSD7iFv7fmukI00LwGvzG68v/CHPyrIxjPcmltO4X1M7A5dJUOFF5p8pc6SQvO+GH6\nZ2pG/4vbJ86IyMJq6ArIqy2okWjLx+tOqeqS83m9UZxns6N2jnb6oboBlXG2XDm3Lf+8+JyD\nalJIxnBvzqve96eJTHlHxG5ox/+Llsy+Y3iV5cvnvIvWvI73Q1fpwPhI1HzXTW6kqnTwHHv0\nwZfjDUpw4xuH9qrqCiiuLahtvOr6Z1z1WvoCNhlZ+JoVUvEz/OXKM1GBzS6dhPvxf3bq4KAY\nkrDjZlKAi+S69/3pK/0imn8QmUrS86fSwdOYwgqWdd5Fq1/DxtBVOjAmiirGLWXsJ1pwBuJz\nOlgpu/0v8GtNey2idQVU1BZU58eGequ+mnX1BWw28jkxK6SYgicZu780K/IH9o3c3L7dYK9s\n2vlgA33nBrN3WapqQVDq8/+l01OivqMXMI0Vr+e8i1ZO8mqEaTtiNBoR82mYQGGDY08a5wdA\nGv8L/EpTTITufNSCK7N26U6p3UBfwMdGXpBmhfRpmtw/76+OVKNvBlyMAVJIPuDhBAxm4nLW\n0NJwV+f/Tw6ncPC//oOZ7Ov5cPwiL5tIOYKSJmPUOr6p+gM7na9idPd9rEEJbpDriYuGOE3c\n1t/Wn1K3sX7tEyO/fNOWDbvj4yPQypshsmfunPcxAC6F5IN1QFSEwUXMV0vLHsytM3F6BE3m\nn7lN0aTeRbx212TN6MXLNgnwolrH2WrvxhnRUt8yiyrodyeAclfqU3IIWrutuzSs6jdzLcAg\nZr95E6H9mTDfzxNvz+vdad7duwOjke7R80YHSiH5YC2QOoXB/sJ1VZ8lCMO0358HCuNPFjmf\nzIuy624cb45qtqOleZqhNsqcjwoXEzn84md5yyj5UXq409lt3cVZsqGLJ/tXOOO9eAts7Q5n\nz+/fA+kf/uvYZQJyNCyEXAaDt1JIvlgDZIox2F+igRYUXuTOOvsCPZuusdhFdD8U0N04ngOo\nJAGGqRV8Xf1JWK7tSHC1Nj3qZ3nccKHiF5nchPMEBpTUr7vYHjZupV/7xsAoy5SQyqnkQAZ6\n8XnecHTZd3AYYh+5xRJm6XOSeDhSCsmQ1UpLLa3B/jKttFEqceOcUxpKT+xmLMNS6rrr75y3\nQlbnAHlGreAUNeTlEm3HPZ05gsKPfpbXlA6u8kA+gYG40k1bjoiJ5Mn5nOc8ol/bz7NSeMGM\nkIq54vO8kqXuKb8nZXmYgITy5Q2OlELywSqgUAaD/RWf0CINiXvuwijgaWV7LqVLdMo55As4\nAhIkOQaqFXyV0hFCF8TvtvbrIDCO/uGkIR1c3cW+CMgzZipu9VRXKkzLHeuqyxYu0b5+ijAw\nOAilP1JsN/rfTmTy6Zra4EgpJB+8DZTyEl+eU+05zSSG29ng4mhgsLL9m2vKV566qe5WCvzr\nDxH91ApOUC0LJ6phWv5apbVXBf7YdxL16OCaTLNkSEfmDTkfZm9GJGh54HuxAllcvSUfetSl\nCKPumBkhXXPF53kFuQngWpFCuJGRlZQUkg9WApVyGOx/ZTtjP+jutr/HIJWjLX17YFqnrdmb\nIahtotCMBF9WDaIKVBPb30lN4yZO/A3/XVs5Nm1tpvUPq1E6pBcZWxDD+qqbnmTFanzuck6r\nLn5X14yQ4IrP8zrrglXvMwztJ4XkgxVxnf+Xx8cxR3XfzZXxeN7pVP5MAaf1s7c0JbbTS63g\naNWOI1sZsX1lFFBa99H2+lleDaSeXawe0zRYg8ZiXmLsrXj2tLqpLytT1/WcNo/7XV0zQnrM\nFZ/n/RaPzL350pbu0ZFGrplSSD5YlpfVLuDjmBO6u+3qFL3l8oxHnFNJ3jLQ2Q4fAoiIpKcG\nn37OoEbLoWQrldWJVZoW8hZEwZ2qSM9KNaQwDJxaFAhlDGPLszl6Y0+zSo1dz2nbw+/qhjRA\n5O898wtz2u7IbWhRJIVkzJtZ87E6RXwc5IjJpXB9Jo7odl10eg94y4lqO49xpUTjeT7YD6RW\nvcrfAp7qESMs4zoMg5o42TeVkJGVbcxKqZ+7NRmDK83Gn8exIeqmAaxGC9dzOjzhd3UtE9L6\nXn6dK8xavt1v7EwrhWTMcORn9XyFdDunE9LN+S5R8K6I4B9E46Rq/v0o1S5tGgz6oVMDWoxS\nO9ULgSODs4um6XP7gc+Ni3FQHplZhWZMM9l95SC03KEj1E2DWZ02bnXo43d1TQvp9JLpxNQS\nARi0+0QKyZghKMgalPVx0F/I6xhSuLXUJebQdTRwaMz//nRo4V4UGdIjd1Z12kudN5sH/Dy0\nJHdDxwvfw2ugOTd6Z0NWVqUlq6B+7NeoC/kK3/WiaoM3lDXq4HrSZv8d8c0KaZ8WSwPPBFyO\nd6SQjBmEQqyRr2i9/2D0y9qXc+cdlwgPd2MGOIT0qNcC7KUNVS5bZsRGqeMDUWL7G8Dx4TWF\nrc+oQ8AOv0o7BYrvUP1hVln92DMorPOrfN9YNcLdcNbCd0ffG2aF1CpixtaiHb/eXq+5z0AM\nASCFZMTN/C1RmDWp7uswrNDyXOLeRlfH9CsrHAacAWQYCikPUeVyU5hvzUBOxD+dBZzcMEV4\nyY4+rHdBN2InKOJQzTYUqJnzJkWjncz3TUSWHPz5xtr4P7jgjlkh5VAaGBPqMnYpq5XWj1JI\nRhxFRRRhHYxsrIi7WOUIDsm2urkBrnb4Vrfxcrrd8DD3BfLrHB/EJ5gOMsIWdrdjf9K7oBtB\nVkZ5WJ12rKZa2EIKTfQa3/ca3uS+W6NZR//7RO6YFVKq7kol09xjbEDdRNfhQaSQjNiOUijG\nbvsMfhax5pJ610SyT928l9Y5zAMeDlo9zcEdhYp91cIpJOFaPxVkhC0qP/6o3gXdCLIyysca\ndGB11MKWUpIxkRZ+Btb8TJvGsd2JTylgVkhFWtBg6ueMTU6X6Do8iBSSERtRmGIR+yR6nRr3\nOzYFuzLddd97yk0qdrbwfLLtcNu4iqyrU0jC0m0yj4yZn2955Rjwno9yBGRlVIA17sS4x3As\nsIryx4qL8gbW8zw4r5qprlkhdU6x8S7L3Y8ltPY10R4IUkhGrEcev9KZpNmgpnQp/WDCgs2O\naAVNra+gJdSjytVl3Z1CEum/JoKMsIvwLZOOA+/6VRpFiynEmj3GeCqXrMC6BKXROJPvW4gN\nZ+Bo6CUSs0I6HoMVrCfaNkRfM9VwQwrJiDXIhpJ+HFf+a556IiUef9B16SOkrC1uzwCSR4YU\nXr2HHJZCCuKeGM8XREaKKae95f90h4wjirCWj7NmdF4hiqWSSrOPWopNPH2HKSMP0/NIhwbu\nZH/WAppYGfdHCsmIVUiPUv4dSvOWpRa986Dr0g4UUnsf9SyunVX8jyrXifVxColHln2vL380\niVwUr5/Tu6Ab8Q51uFjrHpQbKRLlaYyicjQ53jMypd/Mk8nOMVNds0ISNt8JfxhE/UwEUkhG\nrFDa+GX8O5QiV5VjNx5MNrs7Zf8XxO1Z2+LaWUU18gB5ymEIBzXWee6cfNRBzKtO/9stWolX\n3laOLsnaPsFakYuW8sO/nV0aqxpRr8WHvDPpb8QEj5gVUnTD1w5ZOYMkkEIyYqnym+rLrEEl\nC7ykWU34mf0m5vMDSGccUiojE8acc3icK3ShtldMZp6hokoKMkeYeU3ngm7Enwuoq8g69GGP\nAJnREil307C3kM57+JhGHsw5C5sVEg395Oy1xuL7XgrJiMX8MeMXJZRHUlUv+86Bp0rytttu\nKqIZuZePdAqp/AAyblI+0S3GaqSjGeU5t3Uu6EY0oICqZdnL01l7RORFF5xIoFSWwj14K3Zw\nx1m/JOkN032k8+sGlotAZPWx/pqz+4MUkhH062rkqK/j9mNADS/7/hYe25W87LabciP+oFv7\nZaeQij9F8fRjuYlD7RyUmuXNhAjM2OW7LFY9i3bNOiFNcQzkOfmmYzHfuROfsi8LAKvNVNcS\n6+9LHwzN6Idjn/9IIRkx11t7zQPdgVpedl0DTzTkpyRDTfMMsxMiVjE2ySmkfE8y9itFELrP\n2KahlEhiPotGPX9SJFWN0a7ZY5j1HMbxUGaz1KfZNzQPWtXf8T8vWCCk27sntYgHjGJxBIoU\nkjsLdBHz5wTwHOnlfVjulpiS9XPYIsTcISf41Gu4RZBGth6MHVdeeRrMZWSasZClRelMfhTH\nTVUr01I3/LUI8/h8wJtqLLJD5NNU3d+pXS+YFdKOMfUVsWd6ZMaB+2aq4YYUkhv39Jn1Zmo3\nhR/09j5RlAA+9OXPjFTouUKDaGW/4MbeGum6Uv5KgD9OVtJs0FssI3Kl96M4/kl50Iee+Gcp\nTnInrIVqdMxj2M1H2z8zU2GzQlJE1GHOD1aKiJBCcuO2Pv0K/UhX8fPEfkATb/tS1qQQQ0VN\nVi04nNXiby1yCim6k0hMwe00ViOqJJayHIg1iu+nwUOT8s5iH9xYoVrtLVGHzn/HN4zV8tvV\n1jNmhRSFyEqD1/1hqg4PIoXkxr/6nvDUAMbaBhgY06UeQfY3hUxWLTgc04bjVggRcY/Y9iI0\nEg+cvw7FaylPlGIRfsTRv3+cR0vhncVBuLNadchYoU7m/kVRIesY5WzxA7NCuv7Jy43TAgW7\nLfA34qU/SCG5cd0ZH5EtpXDevpyRNJ4xMO+u/S25WeQ3WzfrubaZfa+NRpNJAiIiuNtEG8bI\nQZw/gjbgy2tRb7O/q+NBQ0J3Pk7PnWzr0PJwJKxTXQRXYy1/vdfjLzLtO2muzhaM2t3dP6tj\nBjlqF0z+Ue0rie6OZoofPGvocHQJ0chsqXGXJWyJpbj5ot31Ln3a0l15msGHRNRLHtRgE75j\nsavpSRLls7yNMTwvX31afikF26AmVVqnTw7VwChCvh9YIaQL6/qXAowipwaKFJIbl3U2/q0C\nsUcYYegCS9ObEX4H/Q0ZmyISdmrTOjzv4KOsEL00FYlg+fjwFvzI0ilPlPqAT8uatSm5sTgf\ndXklhv0+UWzeqMsCyBq7+OIHjukcslxEKD/ik1um6uGKFJIbf1EINhVuFl3TzxNHItIguskd\nUEx5f2OVhoyN+PcTqO2urfRpe4pwdNV/YnuUFx6r+SMcZ/m3kQDIZfGOYZzfVZFch3zU5XVn\nsswP9DlcWqleGonF/KgdsnVdbpjsKBFIIbnxJ0Y5lrnhs7+mpi9h5EmD3RHUZNpjcIAtvIvL\n2zRHI56J4mk1HF1xRmEdeazm7UpTjHJ/NucWQ+MN/XyXgbcMedawOc75zq3Y6Tyms1FKXj8w\nK6QGk3QTSCMNovUHhBSSG+coTqJKcUfH2Q/G6sJEeyAVFfaefwbUoWMtzn2kzY9Snj0MY+W5\nkOJ40ifuQvqZ8KpgD3Mb1oH1jcpbDJ6DggfJXpTVsXmHPkrrkxEGmUT9wNJIq5kMEjEFhBSS\nG2d06aR4dKq6fp44wdg5II5u0JoBpAYPCe/g5BYtGAM9gjBai6J1Tek7oSBt/0KdDHqEe1V0\nr2tU3jwRWJY/tdYVdGzeCV2IhsEZzdVZCiks+A1DHMs8n4K/7nivGidAykTJTYoZ5f6zg1XY\nOkoLD0SjC3iViZzSOPuJNoX8Q5x4gnQABRpr482gkDNbhDpvTcv3nPfol/pkSCN95/cyRAop\nLDiJQY7lPI6hXD+Yolo4eyEHRVzNF2mmakFgBRpDC6H6PX3aaayWENLJ7dCMmm6LYztxz9kG\nhqOY00UAyLZum/fowzjPNRlNSQopLDiO/o7lnI6hXD+YZpxtef2nSmc9G3xG9goty0DD1Sf5\n8o/0aWezWSI7+1EKq+Xi1NgVOM9YjerstvfpsCnkbBuZ0n0e4FuTU0cuSCGFBcd0sWWyOjrO\nfjATa4wP+AJKu+dm4msWDJYgBrGtxSDWMfq0c7VMmIeUvpOr5XsPpb3HWOUqbIbb+MsNp0pe\noVMzxboHZ/4BFgZIkEIKC47gSXXp8HPcHe8pP0+cA8P8ObwznwpWjbZaBLkAa15GJ+nTLmJs\nMBfSPpqfraY/9klQtsryldgrbp4lU51Tbdw5sGhcZ7e3ub+TWYcUUljwI7So1MuzUcc54wI/\nT5yHLcYHfEOxDxytoks1rxodHCLIBTinunweKYClWpLzLze6T0b3AX5lrFR5Ns7N+36s0/dx\nlHJSigaZugazzlJI4cDHA6AlYVySgTKabPX3zIXYbnzAfro/Hdb7h1zSKNnFPG2yiNhfAljJ\n2FAupE/fdR/6fwr4hbFiZdkYtwhlLzi7Us8rJ/X7J0e3YNZZCikcGJDekcZoYVryKPChDidL\nfCXiInNqZyrvXTiaqApay5vQG6WXBvXzRDShrWuVf430x/YHjib8WagUe9EtivOQkqc0U4Fn\nQVmH8vUMZp2lkMKBLlHoqC7OjU4Jv7NrkauAj6A0h+n+PK6tbcYPiaqgtczWZl05Fbi10HAu\npFEjNFMfjYHA06/H5y3Bni/sWsjTRTNrrdoh3DiisP95LBOBFFI40Axopy7OiaBodEaZrF34\nCD4SLPDc5z9pa2/7OjwkkC+9M0NuVYovzJ7jQkpJvyIP6Y8drPTx6iG2GBvu5lj1RME0CzqL\nyaZByknPs5KJz9niB5YKaa45uz8nUkiuVFen5RnlICG+8vfMPThsfMAvVNxB5Ub4jdYWJgkL\nVvKldzbUanEjBzUurELUI/pjqe9UAyjMhrplcXgsb8wIiF92Sk/4Iivv70hnojAtpDs/7VKx\nrE5SSO5Udv4Mv85vJr9v96M4ZnwAH17ez9gkPhY2H1Z+jYllKvQxWRrEYJs+UGTzKfpjqe9U\niVqCg3O4FtI+Z8p+NMXEeOAKjGFV+7MgYlZI3xdwfEDrKiWF5EYFZ8dgsphP8ffMW4N9TLb+\nRsXtVW5UbsH2pv+9ryAyBfooYU0zUnyfUY77bJvLsdRpKk1JxPpnZUzfLn0oa0RX8Mcs66sc\nM4HVGhjMOpsVUl00e3W6wLpKSSG5URZorC5O5DeTdT2ZP9QH3FAeHm62nylZgwsFhXTGrXw4\nNz0mRzuE9I3LsdTkK0Kj5U9lZEegMxNqmh5tVDOjJ5VjprAGg4NZZ7NCStPU+hD6UkhOfuLj\nAMpPbgN1wzionRqLuEjF7VaaP1E0WDzDz0ySwYV+LJzTqW2L0sjjWIeQXAfoX1S25KP5297p\ndMZzt6+yRrFoqA5HUo6lGazZ0GDW2ayQCg2zri5OpJA0HucWDSWcs5Dil9m6Qeor3GCAbNbI\n33QaNlhWcuIZD33gvk4VqA/njAH+u8uxLylbspNFUa807EucUreOfZg1iEQ1NcQWhYt5k033\nL7dfIjErpKdK/mtdZRxIIWk8wu1aijojeL8Il/Fq09yAGE3vRI6m7DWsuTfyhmWFJ45ZbaCP\nN/Z447V3SFxafnPXW2MMeH72NL27pWI7HBNi3epT6syS6nWiPLSLWHAxHdeuSs33fzzCsa5S\nUkgOmnCLhkLOsEFiPsVcMEM9d6i4zxhrTY6mHz+ElX/YPidbNhX0YZKe4JbuE5FWFZLrLzc1\nddPQ5oei2GZHs69h3XlKvzKPOvbfBSZztviBWSGdKydH7YJJTW77n9/5Cy1MZY4bnBIYCVTc\nJ4piKYqO0mt/6zAOWFZ44uCBTpzRXfrxeaPpyCVuM7cwdhOUTSloewUkrHf8BlSvGcGfVKIv\n+Sj8zZCZeMwKqTWqPvuiwLpKSSE5qNCB/ud1xCh+TWR+/dW6dyBbge0UH+4vxjIDSh99r3WF\nJwqeaNnpS7+d923mo6QQkluAiYna73h23F3h+A2ozIOlpBSjm1OileVg9/3MCilzXTlqF0yK\ncv/oXI70Ezl5EGynlal5KG3fxxQt7wJjSmcjLR/DsxUKyexqmcrI/bwWSR4R2Vy3T9aElBr/\nLnTMr5UvIjby9YdoaXOQK21WSEVHWFcXJ1JIGrl5wOHsjuHgDOIGsdBHmvI1b2Xji5M5TRzU\noQdb4WGSmrltfBeteduu2VrX7a9pQorAtTkOC93SOcVGbgHCAwFuY8HFrJAGVzQXDswzUkga\nWXhMjixKy6UDf/SLBxKssg5WIIfbLX8LcfIYIbYbN3BjGXdf+o/QqwR9eHeDudcdfXT8PdNh\n4FQ8XmziD1ceZjXYpk9mhXSr2UO7L1zkWFcpKSQH6fgNxb3Lydbnvvrjay5OtQuU5+GRRqK5\nmAqh+PH2BQ+L2tpt4xcYUZYeSe6zqjOcQjr/Ov0G/ElBKgqlEJu4fOjptCnY8V3MCik+jeNz\nWFcpKSQHqXgTJz1dX3ICv04LmdLAwgQSeSKAApE0gPHVmCj+RfpwTg86PN5YO7eNN5fPqE4j\nxKPcts9yCum3KfQb8DaFUs2nbuJRGag5bHVQ7QcwK6S+TqyrlBSSRkIEj/zO+y4U8oYb9Hwy\nyGTAdxcKKvdZZir2l2kFxd23yfdJQYX3b9xD/iiNnz8aKtsnum2d4xTSiYno/zFblOGX/Uwd\nKhcJQ+k5a2V7ySOW+iNZhhSSyi0RwI73Xf5kqq32xfGwMERJlUpqPryfXxNjDQiqKY0f8KRi\nnnJojFDqOdNt25tOIR0Zj5S92Ky45m1YNnUTtVLva79CQcW8kO5/t3bOZusmCDlSSCpXxHwK\nv9EpQslx3qmeZDJzggu3Z6o33U+T1IVgz136ggfq9hippCkeiMA83ymkQ2OA7mxybJGHRKcS\nIkjMda1dHFRMC+kznjAaLSy1K5FCUrkg0k7wGRTyreHhEi9Pg5UGjtpv+g8T1IWVFhaeGLgK\nenna0wId3Y2jFvIqUx8P344CHmNjU2Rr8os6aMe7e3/RQtDtB80K6VAsms58d05LZPnNukpJ\nIWn8JoK48fuErBmO8F/XOWo2YWtYqN50mZqpC0stLDwx8Lmy3p72PPygj/1i0AgJP+XrF4BO\n7LmI2BTptCEwygVPiXJhZRo8j5gV0sPqZV/isVGbWKSQBJ/U5sliuT0c9xnnkbCvz8d9X2cG\nwDKkFHeddvcF21DaFzRFjH6e9rR+0Md+KR8p4cMkddsAHXikkwj1E/Ews2doIRiznS6YFVJ2\nLU99FSuzY0shCWYLG7u7og+j/LhSWBDcXBJh5ZusQna4EPgdYS3czNujX3jbB+0Al8fmBfIP\n4RXPBTw8qaf+o1C25VO0EAxDNhfMCimnNkzZMbunQxOJFJLgdWFjd5vfFIdEeB2lmbLSdyLv\nAFgfVwAuzLay9ERA1n+6fFA6OjyY73ZDofzAk7wfRHaC8ain/yg0OUsDNJZeMI+YFVKH3KIb\ndz23QfLsgJFCEkwEKigvN/lN8Z2IdAjcWRtt5Ztc/qCQq5CsjL6RGLh9hUfP60743n1TwmWl\nWdfnKq84d/2rpv8olNSTIvelCnqlzQrph/RNqO1+rEmMlcb3UkiCsQCFhucDuNSq6cwX7r0X\na+3bFHEV0hTfZwQV3sF53tOex+mx7E5hpUP1r7P2ZfUfhTrwFEu28IOnWYwZITUkiiKiYM2C\nEahlZdQwKSTBC0Bp5eUfflPs5nkeqb2/v7K1b1PMVUjuxgOhhsYoU7ibAnF66ZNVahQFBtyP\ncNTe5VeBZp2+V3QU1EQUHDNCyuSKhbWSQhI8C5RQWi9jKIcReTe0o5vD+kSVJVyFNM7yNwgM\nIBpZxnva8xQ8BDRQaj9ItVsncus/ypuMEvMZJ6S2BjtMhK7tPebDFlcKSTAAKMbYn+ATJZ8y\nRlFBkMLytynlKqSXWVGpdAAAIABJREFULH+DgLhHn/YDj8ZxgzzFjS1FIxPZHLXPpP8oZFC0\nJyQD+qEU0otz6f/x5soHjHnW0GZDCknQh7fujwEpc5Ld2O+t6OawdKSBU9ZVSC9Y/gYBcYee\nKp6n95/1FKyiHI1MOMdLUus/ylRGyctDMcVsVkjVNBo/NtRXQGqes/B8ZhTp2rMUyt82OFIK\nSdCdpzfZB8QqN8qHRyO5OVaM5W9T3lVIQQlV6D+3lMewF4erF9TQqS5UAkYwZwyeSP1HUbp7\nC1vDOCG1NZgVUk0KSUFT4umUD9DauMXGhdQLo5Wj7k/EywZHSiEJOlNQa7ZDubplgA/2c2sY\npLb8bSrq771UyG301QSfG0B9L1ltx3gKVlGdnqF14BHlkzyREVgd5Coz80L6q1yFLdfY9Y8q\ndrx9cgBmGJ9HQipSgpu3JJSsanCkFJKgI08B+Z7S8K8KbPxG3BxpLX+bKvp7L6NbAqKg4c3M\n6RrQ14tt3ARPwSpqkbffT497FNIoxropbb21D55lNWaF1CO7uOX/zvY8S6hT2/MJ2nkkpNRq\nbukuRveDFJKgPU9KvB5oPwDI30XcHOksf5sa+iZRHqCp5e/ggaPxXhr3V9BueYRnk54pnp5U\n9YDRWkY//YOV5nWfu7eofVRIPKzMCil3J3WhU3HGXspgfB4JqXwNsVK/nMGRUkiCthTUmq0B\nTmxT7ooy4hYxvsiJoTbXp3oHKh2m+pa/gwe+8OLm+0VJfL/Pi+HmdE8WCo15C+4FNyHl5BaE\nQ0/xCdoQ+PyaFVIeLUtC/ayMjchsfF7m5xd9NjGSf6qP8KTBkVJIgjZAFrIqxSmlnwQ1EIGV\nE3aC+lRsDvUO/LiDI854UNnmZUBhlUGKgDdyedjYnJIf8WD6espF0OzYwOP8qgU7qB0zL6Qu\nQhfsg8j27HqBOobnFRCxNZRb436nqBijOPBSSIJWXDYrgN8+hep0w6+fxVAMIfCwjIjA7t68\n5RB03vcyxL3SIEXAAU/TtA/zwbmxiHERUv/PlG4lUrYFBY75yKpKe8eskH7PhlYzVs9og3S/\nHi6A94xPvHNi27wR7euSX0BRwyiEUkiCh4D05HKDM59DDXGtPDosfxvu0Te3Hv2Pxt5+utxE\nQWSdlwDmywNNEfAIMJnse7O4CGkYq0kvlflI53YrKmyM6QnZo4/wejc8yD7L95a/Jdz/0dg/\nRApJ0IIPLSwC/jjsvEVKW/42PKbveR6ePy2+GxSEd/DACk92c4xcRANMEdCRz7suQkEXIb3A\n6vKLxVc+s6C+PrDAsuG3bYu2HFeEcc865ykpJIHyqEjD43ucv+GcZ2zg+7wA4ZZHF0fwDhgO\nDiOzpOCz0EvWi8XwNOtqQBfu+PEhyulkFBMzmjWiZ5GweAhBEGYZjisp0wSI5dFJ/mTrCqv3\nSGqP8XVM0Z7Kvfw8bzfixxfImiL4zHZLBquxEF46T97oxl0RLzxdWyek+PUHWXMathMB7h6I\n9GA9ZoQ09E+3HRc8ujV65Gy5B4a/v//WQTcpJE4jblk3GxRZVTM/mGlhKC6VTlTutRdpLik/\njo6mSeDgM9X5nLiiDwA2DzgbUEFPCCNvMfaoQsPHi/sjJU0vwz1/c1AwI6TecUMOOJtzCfsH\nx/Xxu4yTD4Q4Pp5C38S1MCZvGNOA23pP5/ENNfODxda/zWNU7s2XyNarKI5PgJVRA7zyKnZo\ni5ujdLFJ3gw0vnBfYAG9NtLdPnxA5kOlx0cmrJktTALvFVNNu88ro3jfJbt//uPn3Uv6FEXV\nACL+39xuNJIim3aCeqAg2FOBK6r5gcIy69+GkhXjzlggi9I5Pz8ZGa1/iweZ4IwxvsmRRJnx\nGMSBxRcemgJ8lKupTkh5acPHSo+PupYltwU7gj4z20dK2N1NG3TM0s2X8XcASCEJyBQzK+XS\nuqqaHyissv5tlMYRUiSMA/JEVIq4My0IRkgeeNlpuLNB3/aaFWh84WtzxI9LC8cEAUQvbwdE\nlqQyltTXVy3MDjbcP7h8yvNTlh/0L9LatUOaXcgfJw0Ok0IS1KJ+M4VAuS6eTsQ669+mb6pI\npV80ASiQqkY6pUtmvVmsB8Y4I7qu148GKA1Zz6bfXnmHxzhhmx5RfZEiIcYdP4MIj1Teiur6\nIqSjdkfrRiCinTDgrWZUihSS4H+gYbtxPDeS1gXwMemdGPrnyJKiltJpQeG4DlXZfFgcW8Uz\no/CCli5tjX58+nUEGtl8HY+6RcMXPP0NYtW5ti8gfOgrWVFdX1gjpHsn/ImtfDot/tcpG3Jz\nnxIpJD+oTr+vym83bqvmBwhK9qJBZUsNOUEtyOKZlEbSWyEIXsW4lekz6uJqfZLA1xBoZPON\nPA4kPcuy8iuUQQQxY1+pU0tGDjuWYT6Ifvdf2LkySDHCd9uuC5YrTcFnUJsOlULyg6oUqu3u\nKB5xt6UqpI+tf5tnGz+/mX7QUTrX22RykNL6t3iAj5TPo9ktr9Tb8ExCoJHNP1Cf0vPUwCc5\nVO18o8a4q2FFfX1hVkhbInCA9UCzsiQSHxTgVsX32/MRXCkkP6hMlpjXld/u+xT3WhCEDK8/\n8pbVNKD6J5epoWV9nKIHoVarFi5+ud6qdCICjWy+XbXuXqdaCeVHLE898C2E32xNK+rrC7NC\nqhW96/6tuObsZk7f1Y0WF+5cXNbLUkh+URHxwKXhfM6trSqkoGUVngk0ptcNlmYx9Qbd823U\n5SV6P4cJCDSy+S6eBokGF4rzK1QcWevS+gHwCTIY+yRYhFkhZWhAH0RpEDxm7ItEFMgt5t3m\noNV9KSR/KE+t/nND+SOiozoiZeEsgytzgLb0+j4QgnkXGmBroi4v1nvevRxwvLF9asvwB3Li\niyDXxMKNaP3iwz/w9nBI/BTNCildaxrIPMNY5zQ+z3sWbbnxR0JzDLkuheQHZcnx+5fB/NYS\n4YrTPBhG3irepHx3ClsD7qQETsJxCo2qORAuwAbnrjEBj3UcUq27L6AyZfHMUx+Pj1Z3raBr\n1shkZf3CrJAqZbh+O385xm7kKunzvCullI4g+ZpcrI4M8VJIvimNwkDmjJEUyk5E98jqKfq1\nNcxHWh4acnsI0nLtjKYPo/k9zdNFJ7n1UsBhko6pzd17UUrHKz3WHhc5mIlV9DYhCUFhVkgL\nkT8fprMPSvgT6PbqpIoZue38zZdyGDbEpZAEJcGDoMZSKLseXEgFPAXttYZFahzFnSFIFPk+\n/zCa39MbunhZ5YsgLsDCfqOw6ESNzjRkt/Wisx+5lt6mhcnK+oVZId1/KUOKzreVVlv7awGV\nce9Xo9EnKSRBcXCb7/TUbH5SmLvgRLDebIlqavAlENh3mQjW8A9TQl2brUtbmy9DwNFd/nSk\nH3uDcvftuOS0OHqX3uZhc3X1D/MTsgnUoD522tKUaFJIgqLgpqqPUMunL7/3Wq+2MuulC8tU\nM75vuI1scFnKP0wRdW2GLqZwrtiAg1L8m0n7cVkYpTzCd95t4wirsolfM3N19Q8zQrrmioW1\nkkISFEZDSkP3BC335/deh+C92UrV0mZ/oFajiWAu/zCaA+E0nW9Itkhhup0orr6Lai5efFvo\nbdomurwAMCMkuGJhraSQBAUj+3xeCeBuXoP4RbYy5bUbq1V72EMh8AYTOTw1xbwmHIo4GWHG\n0/0Umrukmf2I3uZRr4dbiBkhPeaKhbWSQhLkf+Uc2ds9TctD+b1nvZ+5gzXqIPRP8BJxzkIm\n8g+jRqmbkU24uHLSmbLW/huPuYSC2BHka+ZExmxIyuRdxv2QBtEyj8mbsW/w3my9Oi36C3DO\nx6GmEeEcs4mVOmr+5wQadU8N/C/x5d7BQBzWrX9Gb9M78eX5jwWDDSe//pNZnH1dCkmQewUP\nRcBDYfCYvGsD88IOiI34kL+ehKdQ9dYiInWrxjCl1fzPC2mCNhpoaKLgmPERJ3Wru+htBpgo\nz29MC2lXcWAjKzTUMHFYoEghCXK+zSMJDaflUXRPfB3EN9ukWtqcCTSMTyKgDl8KCn7Jlpxk\nxUVCMDaK5vQjzSXDyPLWKf3qbrpoz5ooz2/MCunH1GnaKUIqi+JWDplKIQmyr+Ye1DyF3hi6\nJ/YF8c02Yyd/PQ+c8nGoaWgsPyf3xC0wenFhHiqVsX6FGbsPpB/t42QjersGDNpLF22kifL8\nxqyQukbsOakIKWGapbqXQhJkWcvdJ7jlzni6J4IZDmeraiDwT0TwJn01yEyjAvfEzV0pc341\nkXqHfIzdtnZs4DvlfVKHJG+aWSHlbMhISIz9z8rwnFJIgozv8uiNY2mZD3QFzdCOUdAd9Xn3\nJX4J4ttwyAK3Yww5EGbLF5cb4MHxW+Tk6fp6Wvg+B5X3yT7JwgK9YlZIqXuqQuri2/rbf6SQ\nBPGbePTGCbQ8n4TkOVy2NezA92LhDxwN4ttwyLlq1KfkHZIxbaocEHlQG2SmLGOG+X4C5Ucg\nosh0Cwv0ilkhVa0lhHQ3t5UhJqSQBGk2c6tv/pP6NQkpmHf4Z5pMz3vPq2IV5Cc09nNyhY1D\nRGaecu/4hzVjmv/7F/CUhe9zFGljuoUgqYt5IU3AFhLSvx0sTSovhSSI2cpYT+A1vrIaKQPM\n0xAYX+CYWLjoMhUTFCgk0vivyO8pBhREaxTb91SZSsDx80B/C9/nOApan+DQI2aFdLd2irpo\n3jEjygQY+sUQKSRBym2M9VFnWdg3SBNgnobA+FIbrPsbB4P4NhyKdvnqHtS4zqK4U+sLrGFE\n5lLAN2fU6WeLuII6XrJoWo3peaRb0yh0S6aXLLW8/68LaapqbxX5KWPPaDEh9yFjUCd4vtaC\n11/2knDFQijO2JRvgbdfFXaaI9j/EBEHfHgKGGrlG6Wb97uVxXnHChOhq4etvu3/60IaLuJ1\n3MfnjI1GGXEvfIfs+COIb7oXanaRq/g2iG/DoYwA0w4ALdSI18PUZBvvnFCnn63i1aD5Qbph\nVkgjvCbONcN/XUhDq/CXO/hSeTppUeZ+RL4Aw8sHxn7NDelG8NOgVFBEM+sHoEZKIaQhjLsC\nY8UvwPPBfvOgYFZIQIVp1ps4/teFNLgUf/mXTIIWaCHtT6AoRVwNGrfXaAua63bwKKOI5o2f\nyOFXMIiJ1HpLjtLAQzhiVkjrO6ZBVPPVFjv5/9eFNKAAf7lOU6Tva+5vZ1A60LAgieNe8GLn\naZRURDP/Zzjyvg5gIkjqwh+BMcF+86Bgvo90Y/2jaRDX6zMrXaD/60LqJxwMJpJJUIJmDvwX\nKuUMzdsHP3lxUUU0i45DDdYN9GOZ+evcQ/Anik4SxBJ/JK6lxDsIP8h/XUi9RSCd9C7j0NfQ\npEpo3j5qh+9jTHGMGnJLT0LNwwL0ZWn56+wDwCtBfvPgYI1j36mZ1aWruXW0SB/NX2NdZkbv\nYlXQw2QJorVA/e9tC0r5/0ZSIr0Vv/MpJM6TTIw6TP9WtQQPOyxw7Ds0riIQ322zl6MTw39c\nSOkRxV8jXU2CooKQY8wjqTOoUX06+J8UOBD+4aJZ/Qcc9LwvXl/bq/omhR1mhbTr2YKkog+s\njc353xbSFeWOIpfju3A1w06zwcsJVhOnNa/aWGlA6uSS8gGjsfaCU0jd/xWvE7/W7DjCDfPD\n3+ket1hF7L8upDPKHXX3fJ+E68Cv+u3Dgu4mpJIeqgtPSytdGpxcVD5gLmz4yymkrlfF67gv\n1fgNYYdZIT3+fjDiRP+3hXRMuaNufY4bf4fA59sjmYQrIWNNghOA55zyAStj02WnkLr8xR9S\n6NYbuohC4YQMfpL0+F65qW5swyWlD3HWlgpk1Uz561sZY80JPXJbYctVp5Aepf5SXvAksAuD\n8p7BRgY/SXp8pdxNV9/HuVMhCDDnkRwYIRZqdQ5K+adpeCHHNzcdOoprr3xWSlRJo3i+Uz8m\nRWTwk6THduVu+nYtTv2M6BBk/PJAHs0Cu1rHoJR/QvmAAxMoPoNKibIUerW1GAxf47uAJIgM\nfpL0oMjvEX3x8w8oa08F8ms+QRXbBaV86gS+QKZIKv97FKmUl94p+Nom3wUkQWTwkyTG3VNs\nPd1OzXHoO5y2pw6FRJBkxso8EpTyjwAtac6XPmes8vf3s7RUeFksF1JIPMMtRwY/SWKsib+2\nmm6ncti3F9ftqUNR9GGnPlcWSrQKRvG39oD8Qxh5xyK78neFB16dz+K4kHYG4z2Djgx+krR4\nZhCOLqfbKSt6ZQ9+CkrPlEQvNp6y1BduGYziXygBkVKa8l9SIvJrI+kTL2IZuJCCGU02eMjg\nJ0mHW3MSWJ4S+HEx3U6RSBeS7OKeKINu7MVqykK+ZsEovn9WCB9casrVUf7+fYU+8VKWhwsp\nmEEwg4cMfpJ0+B5nWY5YHJonuuARiLCpIuXxGBtGluY5m7jvsmLCsE9aiBB61JRrlxK4M4M+\n7wrlfYmgxwILCjL4SdLhWxxiyo/1gdnaaFZK3+cEhUp4lA2ilONZ3BNDnI+zIAdZz0gIs/b0\nyoO3q/KJ7y+kT7uKNVT+Z5tkU3vWJDL4SdLhG3y8QLm39k/ThBRrU0Wqox3rS+m+MtRz23PQ\nioBgj0ONdJktEgN21oiMYKvo065lQ+NhqVtbKJE5ZJMC63js691oTzfU3smakNLaVJ1aaM16\nlFEW4mq77dllRYjKTlDN2qulpUmjEilEzuR3GXvWmVc23JA5ZJMCw0vQ/y/wP7qOHzTTrmh6\nm6pTHy1ZZ4q/ElPTbc+HWjRWM7RTPtpJWhhdB1sZK5OKbVMnYp8zlUDWVmQO2aTA0Bj6/5kI\nqtPT8dOU2abqNEZT1rb4qBUsRXX2k0u8tXdgQZy41spHE6H6NmAHY5VTs0+Vpy82M/YiUMp8\n+bZgaQ7Zkf+YqouT/5aQEqY+SXkZ2HYUIPlUcwgpu00VaoGGt1oWSZendUQV9qRLHvXFVuTD\naAEtS+1mfMFYzTjlWYycqbbzZGomMjHbiqVCymRVhLv/lpAuowrlZRjbGTzuaEGHkHLbVKFW\niEvfoFBKFEIl1r2Nfs98KzI0NVY+moh0uY1mX+unpwyVefff5cnUQhTfxXKkkOznAoqRDUOT\nKMSQfDI6hBSi+O8PQJ2YgvnIuiJNm65N9Xve1HIomaG+UvxlvrQT+xlrloUyVPJBhldNpTS3\nFSkk+/kdOcmqrq4qnxQOIRW2qUKPKu8dlZ0blEY95DJwN4vufLPUUooXY7xf0QOudX7KUFmE\n1qcCdc2XbwtSSPZzAnH0C10d7hS3qUJd+ZChqEPlyvo9061IB02dQGEHs4/mkzqWZj8AfNxy\nBtDIfPm2IIVkP0cQSX2G8g4BpVJfS9tUoR705jFqHVyG0aZaEV+/klLsXb50kNI+d61OfhU0\nbcXmAM3Nl28LUkj2c1CMYpVwCClLRDR/rWhThXrTm6uxGwu7zJBOtiK+flmIcGP0E/I7Y080\nYr+oo3XzgaA4boQAKST7+Va5sTqvZ87RujaviEjYdW2qUD9d8zJ3Lv2eicKRyByllH6gWLo1\n+R5j/R9hJ5UmJK2/DQTHJzf4SCHZz27lfs02iuV03LyDWQ7++rBNFRqkE1LmbPo94yj1mVlK\nII3eh/7Y9+x3gLw22AdAJ/Pl24IUku38s0G5X2NHsEyOm3eY6pkTnGBYvhmmE1JaF/OKMVYk\nqiiKcm5bzgHcGOlz4HHz5duCFJLtDMkonkJpHTfvSLWZ97RNNfp1iFaTUkjhYvA3CuYTVWwv\nAHdv6osAtzM/gGrvmi7fHqSQbOdJfsv2Y7EOIY1hRXlXf4RdVXpbq4lyh8fpd7yAxOWnuPiq\nY3EH1HacjivqaN2lpiHKt2E91gjp3gl+AeZaFazjPyWkbvyWfYJFO4Q0gZXiqhprV5XWaDW5\nkgKxS+44dwzHvEQFIP/Q6ey7DGo7Tsd1oH1iik1CmBbSZ91/YefKIMUImbEvMXxzldsRAF2Z\n06JhCiuXSbzaxLtaTa7TbJJuxHsocnYZczPwAtfAcXvM8zAceTsCwYkyHjrMCmlLBA6wHmhW\n1tJIs/8dIeVbxtrwW7Yji3AIaRarnJcmROfYVatNWk1uUViFpc4dg5G+NhKRyH6xM400xWdw\n92BnHxZ5KnE1TTKYFVKt6F33b8U1Zzdzuj+uzfDfEVK2edyrAGiT4NDR5CusegUK+PaWXbXa\nolXlXgauawcDkKpSYsztZsDxGHtVKfHB4ESVrAzUawdmhZShAfkfv83YY1Z6of13hJR+Bg/5\noXS2HQF88TFjs9dRwLd37KrVR2pNIigYiz7zVz9ElEhM4LkJcCRZGANPE2S1xySmnkkIs0JK\n15ouzRnGOstIq4khdjKrze/Zhs6Q8jTCfBk1UPGAXbXaodYkJZ8l1uWi7A3kI2e8QBmJS9ri\nCHiaLNpjTyYo6zArpEoZrt/OX46xG7lKWlep/5CQIsexqvyerfOvQ0gUs/cGHrYppwvxmVqT\nWJbPdcyjF5AlMVNJw1RPPibMJgZbUcmkhVkhLUT+fMqz/4MSGGddpf47QrqLF1Wr75rXHULa\npey4g142XoNdak3iWGHlv3MOiHUHUlPAkgCZ+SQcU4x9lRJftqSWSQqzQrr/UoYUnW+zZ9Fe\nhuNKBNcxjJXk92yNq0CUuH35cHPk87AqAkbg7FaFlIFXboJzR1eyCg8478o1VMToz9SVJ4AW\n4Rne2xALUl/SfN2x05Ymv/zPCOk4BrIi/J6tetnhZL6X9iw9WPqubdXaqwopC39c6p4fFJIO\n6wMt7i8UR1otNnwPWGBmlPSwzERofS/TdXHyXxHS8Uj04d0QoPLfQCFx+1rgzW2S/aqQcrAq\nyv8y0xw7OtDWVWzQ+wEV9welhx2urjwOfGphVZMKpoV0esl0YmqJeD/PvnH6H59Pr+QvpOs8\n0cSHQHfVfaLCRaV5J27fg3ZXjrsaEnlYTXpxeuo+QqtLE+LHB1TcKWQGnlFXOsMKV4wkh1kh\n7YvTusjPeD3eySfdisYrh6YuPMQ4qlPyF1LzV79f8Ql5hD7GeAwulD2PqJeQgfK5HLa7cuyw\n+p0W4BF/dKGTW9HqwmsY5X9ZVz9lxyiMygB1vSOscA5McpgVUquIGVuLdvx6e73mvjtJCb2B\n+EqN2zaurHQGehrl/kn+QqpeObLxEDKX6cRElJHSf+DrcyUqRkeksSIqsEmOqnEjirCm9JLC\nsYNbYbxxBcP8L2tNXMJh8lvvq663DddUYsaYFVKOsoxNqMvYpawrfJ43E1U+Fx3oe3saYZLB\nkclfSBWyomb/06+Q1XMaLqQSv1Ng+WYZ8+W0K3Osjl+A3LxS7CFeOc3+ewVvhs76CwP9L2sF\nznxHZz3BtvDhyNbqaEoyw6yQUnVnbEca5ekyoK7P86rlciYju1veKGhb8hdSqQhU6pOtItBG\ndZ+Iy0MRddpl+fV5nLe7cuxXoCJVqjo9PxQ0+x4RTXn6efT2v6ylOLSHzurGHu5D6w8lhdEU\n6zErpCItyL9R6T1OTufzvDi9z8ngaIMjk7+QCgMle8TkBR6657D6PsVYj+zsFVyxu3LsNzTg\n5nZtxHg3/mTsJjXFs/K1188G4vSwCPu/oLO6sGY8sEkzwDbTpyBiVkidU2y8y3L3Ywmt8/g8\nr0Zu5xPpXsVCBkcmfyHlAQp2jogHYnNoOsJvjA3JxabCyiSiieMs+rGo1Mg6SPU6VGrWmqZl\nxUTXlNPo6H9Z87CHm+51ZA3r0nrjmDBNbmmMWSEdj8EK1hNtGzo6k96Z4+wjfdMIEw2OTP5C\nygbkbIFITUO8n3SWsfF52SxY6SKZOC6gP0udHZ9fJeM6hWNnB9Z7Qtkez9dePYHW/pc1B7s+\npLMeYXV4zJMGGdWcLskL0/NIhwbuZH/WApr4Ti6a8BQQX7lJu6ZVlV+2x43m7ZO/kNIDGWo6\nnkXgUYPOMfZGQTbfqM0bIv7CIJatOBma9hUzW9uQs6WyXYyLTDjmwaHIKzPw6ft01sOsBg/a\nWid3Emi7Wo81lg0Jf1zycNyD/PR0EYqVE1tosHFSg+QvpFjlKpTWZJQCFHyUrL1Pv82WxPk+\nO9hcwTOs8OMblKX+vILffijSRIgwxuN+ogjdx7Le9lUM53V8/B6d1exGZZ6Nr2axCKOZj3DF\n0ihC/r3jKWnZwFgUEJFHE1KGVPzhJJ7pq7PYXDVGd8VQVoEHAxvMLWn3vC8SF4mwEmMOoT6b\nO8HP72gyNvMQEDlii/OB2uoVrPRcSzKYFdLWraJrfHNr4Mb13kn2QuLusOk1IXX8gBsQiKf6\nxYBtQq3nXwxndYbS0jCQ6cpXG0VwbjHAOOoAarP6tahP55s3C2HjWvHYzUj5nkam6xeAWUT4\nYFZIWjbQkzIZcyBwd1gt6QSeYjz/sn1uE+7cw3Ns3Bpaep5iR+CLdUDp539TveFH7lPaeTUr\n+ZfgvBuwZrU4L5IGdgtgms9zwhHTHrKVxPTh2Uru0TONOVvOPWztqSIFHcQndyHdpBvLMYE0\nSNiwWenRZZLYkerCKLQsAHyqSKFYzCbVG37YO6jGqpbwzyawI7BSizeZQ1nPp4+lkowIfR9J\n8OAT7O6GtQ5aJXchXYOeYcI9IRHx4oJFZq35NRYJQ4DtK4CCketviOoWBSqxCvn9yzmm/EQs\nWa5+zqzKem68Ebxq24hdQrq5fbvB3uTetDuWSa+j6JHsMXq94/vEUJFvjLrwSgo2GvhoCZAT\nq6+Cz3zFUoepdFb/gqA0ARYsUT9oRmU9B+YHrdZ2YpeQjEnuQtqi1xEyj2U96dVSJ2NzlNK8\nYifHsCnA5kVAPNo3V2eOKb9e0Tj/woDXAd5YrDZiyYosG5YFr9o2EuJRu2uHLqtLf5w0OOz/\n7Z0JnE3l/8c/dwyzG8YylsGgsY0s2bfIrhLZQlrIViqiTUUrJXuUEhVJhTZR+VX8hCSV/kqR\nsvSjIpEl2Wa+//M859w7d8bd5t5zz7n3nO/79TLznOU58z3jvuec85zn+T5WF+ldl0TKX/iY\nqpNppFIsYnZaf6FzAAAgAElEQVRUbjRz5mmYnkzzgPeeB4oqT0lAuhgyJbqFVy0SWO6GpsAz\n8y+ZKzuTi3bv0lgevrBNxNBWu51tHXD0PiDLzXztb3WRljs9at4LiKs9XeaoijM7Kjc+co6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frXSVJ/eiLC9Cfcc/YoTF9yYHZRh2F2lq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\nLBLD6ACLxDA6wCIxjA6wSAyjA/8P+iCbFkyZOuYAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's simulate a simple noisy sin wave random walk.\n",
    "dates <- seq.Date(Sys.Date(), Sys.Date() + 2520, 1)\n",
    "gbm_walk <- gbm_walk + (sin(seq(1, 2521)) / 25)\n",
    "gbm_walk <- zoo::zoo(gbm_walk, dates)\n",
    "plot(emh::as_levels(gbm_walk))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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nussFxWYWaelv1k6gP+8ZOJPaa8OfbkU7eaO+QrSd2e++DRRuVXiiwwmpgNaeAR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\n",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now let's print it's variance at different frequencies.\n",
    "variances <- c()\n",
    "for(i in 1:55) {\n",
    "    suppressWarnings(variances <- c(variances,\n",
    "                                    var(emh::as_frequency(gbm_walk, i)))) \n",
    "}\n",
    "plot(variances)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## [The Bartel Variance Ratio Test](https://www.rdocumentation.org/packages/randtests/versions/1.0/topics/bartels.rank.test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "In 1941 John Von Neumann introduced a test of randomness based on the ratios of variances computed at different sampling intervals. The Von Neumann Ratio Test, is a very good test of randomness under the assumption of _normality_. \n",
    "\n",
    "In 1982 Robert Bartell create a nonparametric, rank-based version of the Von Neumann Ratio Test which doesn't assume that the data is normally distributed,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$RVN = \\frac{\\sum^{n-1}_{i=1}(\\mathcal{R}_{i} -\\mathcal{R}_{i-1})^2}{\\sum^{n}_{i=1} (\\mathcal{R}_{i} - (n + 1) / 2)^2}$\n",
    "\n",
    "where $\\mathcal{R}_i$ is the the rank of the logarithmic return $r_{i}$ and $n$ is the length of the time series. Bartell proved that the statistic, $\\frac{RVN - 2}{\\sigma}$, is _asymptotically standard normal_ with,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$\\sigma^2 = \\frac{4(n-2)(5n^2 - 2n - 9)}{5n(n+1)(n-1)^2}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## [The Lo-MacKinlay Variance Ratio Test](http://www.turingfinance.com/stock-market-prices-do-not-follow-random-walks/)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The Lo-MacKinlay Variance Ratio Test was first introduced in 1987 in a paper entitled \"Stock Market Prices Do Not Follow Random Walks\". The test is a _parametric_ variance ratio test which works for all random walk models with finite variances,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Our data plus an interval, $q$,\n",
    "\n",
    "* Given a log price process $X$ and lag $q$\n",
    "* Compute $\\mu$ for $X$ (drift) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Now compute the variance estimates of $X$ given $q$\n",
    "\n",
    "* Compute $\\sigma^2(q)$ for $X$ with overlaps, $\\sigma^2_{a}(q)$\n",
    "* Compute $\\sigma^2$ for $X$ without overlaps, $\\sigma^2_{c}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Now $\\sigma^2_{a}(q)$ and $\\sigma^2_{c}$ should be approximately equal in a random walk, \n",
    "\n",
    "* Compute the variance ratio $\\hat{M}_{r}(q)$ statistic, $\\hat{M}_{r}(q) = \\frac{\\sigma^2_{a}(q)}{\\sigma^2_{c}} - 1$\n",
    "\n",
    "Since $\\sigma^2_{a}(q) \\approx \\sigma^2_{c}$, $\\hat{M}_{r}(q) \\approx 0$ for a random walk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "* Then, compute something called the asymptotic variance, $\\hat{\\theta}$\n",
    "* And lastly, compute the test statistic, $Z^*$, by standardizing $\\sqrt{nq}\\hat{M}_{r}(q)$ by $\\hat{\\theta}$, $Z^* = \\frac{\\sqrt{nq}\\hat{M}_{r}(q)}{\\hat{\\theta}}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "The test is extremely sensitive to deviations in $\\hat{M}_{r}(q)$ from 0 which makes it a very powerful test of the random walk hypothesis assuming finite variances. Furthermore the test is consistent with stochastic volatility which is a well known stylized fact of market returns! Oh and $Z^*$ is asymptotically standard normal!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "At this stage you may be wondering ... what is the asymptotic variance because the above overview of the Lo-MacKinlay variance ratio test went something like this,\n",
    "\n",
    "![A Miracle Happens](http://www.turingfinance.com/wp-content/uploads/2016/02/Scientific-Assumptions.jpg \"A Miracle Happens\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "The asymptotic variance, $\\hat{\\theta}$, here refers to the variance of $\\hat{M}_{r}(q)$ when the sample size approaches _infinity_. In other words it is the limit of the variance of $\\hat{M}_{r}(q)$. It's somewhat tricky to calculate - as it requires two calculations - but here it is,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$\\hat{\\delta}(j) = \\frac{nq \\sum^{nq}_{k = j + 1} \\big(X_{k} -X_{k-1} - \\hat{\\mu} \\big)^2 \\big(X_{k-j} -X_{k-j-1} - \\hat{\\mu}\\big)^2}{\\Bigg[ \\sum^{nq}_{k=1} \\big( X_{k} -X_{k-1} - \\hat{\\mu} \\big)^2 \\Bigg]^2}$\n",
    "\n",
    "$\\hat{\\theta}(q) \\equiv \\sum^{q-1}_{j=1} \\Big[ \\frac{2(q-j)}{q} \\Big]^2\\hat{\\delta}(j)$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The good news is that I took the time to code and test this really cool randomness test in the emh package, so you don't have to worry about the stuff I just told you :-)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# RESULTS ON THE MARKET"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "suppressMessages(library(Quandl))\n",
    "Quandl.api_key(\"t6Rn1d5N1W6Qt4jJq_zC\")\n",
    "suppressMessages(library(PerformanceAnalytics))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Benchmark 1, [Geometric Brownian Motion](https://en.wikipedia.org/wiki/Geometric_Brownian_motion)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Geometric Brownian Motion is a very popular stochastic process used in all areas of finance. The stochastic differential equation (SDE) for GBM is given below and the R code for simulating it is included in emh,\n",
    "\n",
    "$dS_t = \\mu S_t dt + \\sigma S_t dW_t$ \n",
    "\n",
    "where $dW_t$ is a [Wiener Process](https://en.wikipedia.org/wiki/Wiener_process), $\\mu$ is the annualized rate of return, $\\sigma$ is the annualized volatility, and $dt$ is the rate of change of time (for daily this is $\\frac{1}{252}$)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "gbm_walk <- emh::simulate_brownian_motion(drift = 0.1, n = 3780)\n",
    "dates <- seq.Date(Sys.Date(), Sys.Date() + 3779, 1)\n",
    "gbm_walk <- emh::as_levels(zoo::zoo(gbm_walk, dates))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
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EkkztUx0Dw9+RjArGKCSK+psvOAbCQC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\nUJjtQVUjALFhMcBY4a8chrd51T9C0GJDf/D6hMzUYgNr5mD8SGz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hyE5i/eEy2wzOFtOJZO/I8qIXG34u9mY6S5tTxN8PrQpkI1ng1+4A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\n9lOqmkj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cUG3hH50ed0YYoNemxasMB/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75xN/AWG7Cyx5uKI7RwH9bFlFLdBpwBskiu\nR1ExyXEXoRQbxkNLfNINBzTXahET9OaHig0T0Uf4p1TCiw2HW7Ud+/zYtm3cDrzoCo1V6ZkN\ngtNF/Bh7YzOmx0EU6c0rfWaDjSNWIP2on9kgbrz4r4eF5+7GH33+VeZc3zPpzRNg/bomkthb\nxSjF547jK0nObLhJTsdogyb+iQuYIBUTYFgzG44vOoQpiQEcBSITfmbDnf3xkCsecJebVVSF\nxhIHq67igniPI5R8K5C8AsRiBtrtj7YjlAcVNeZKkqDbQn/GLHEj0hrZIOpZuxwrDWQCXDE3\n42d7xKqjmNrMVjJ5BPRnR3BOU0q0A44DkQVSyy/E4w0XlNt/gs9ssP5aRfwUs9vjM7NBUmIF\n0ia9h2e4WVOvz2JPF1gGOs25GpO98oD4hXiC6kFb68s1pzsPg8YP2vsr+ePfZR+1cDLQ41fK\nqcByJoRIawuTA6PoDZ1liSrn1M5En9kA8mr2iJfyUP76SIkhNiAr5RHr3Ja4ig3MulfqE73Y\ngFlcfuFh4C02fMVf/ZzzrGqb7P7n4gnmpg0mNcICNLYKbaI2WwaKDZh4ZGtBDesjQE5eFNdL\n0KPMLzZ0hItE1XLoEd5jwosNIA+o42YDKTHEBuRbmW7EWUMgrmIDOwvq3cUvylfpxQbMK+ac\nlxHEW2zYwzf/EecRmimjoYt4gmXGg3MRv+8C9uxfeUN4sCRN4ed0eXz9aHEbyLWAKTiRVtLP\nLr/Y0BSasZHKs8OEFxtg2jxkhlcglb/QWGKIDQJxppHknPYSV7GBnQ+tMEvvdL3YMAoarvG8\nUPfe3cuS4Wqn2LBOBkDzgZiSB8/PbDXGcFbRHOvx4QdEYSmof9Eadoj/7SV+SUZF/jLRfo70\nk2GJDb7a0IDdAGcPX+o45hNebOjkp9z+q4fYwHyYrviBeI8inBS4hJV5ZcQJcL02la83l1jH\nfAhvg58fUdYOqXqJers/0cOkgF13kfu/PU7GSyq8TJaAWTaIf9+d0zuYVTIXoBb/lhoQ04Ar\nHTM/yLpTPcQGxu4DrIZUEX3E4OJCDI86MFHvoQHcq7Hwbh6sSgu0MBAgu+VvR7Y+cLo5D/DF\nly8R1W4t2ok8Z21W4dcTGwTwE24p7qcdnCFOnMUo8N6pgmaguLkt8cWG6KkeYoOY3wDPOA3i\nKzZ0wIuM+jBWKzZ8b1eXVXiLDYwNhxTnWdWTgQDZwcou5X8eDbYV9k+CiYy1x+oQIwJ2KWwT\nXzZFqbwx29EJkncI9QEmFG3F6jlSbNjBVxxpaC8cHSDhxYboqR5ig7xIUhyL8RUbusK1WA7z\nAa3YkKn7DcxbbGDsd9DojT7hCvj9gQDJwiSSYWJMQ7if+epBG8Z+E7BrIFPY1gZRTXMKwAWH\nRXHNxUxkc5Viw2a+IvssUbk9nIQXG6KnmogN4vdGVTGHuIoN18FArN5+j1Zs2OyZ9xvR7O4x\ncO7VUCvso+uOQIBsZmICbUhK5CvgeqycmSKn3klqFo32P+QBNov/6YGVPM/ejfMGF1tiA8ba\nh7XgD4phJLzYED3VRGwQN6LN0ZtVLlvG7sRZo0O1hl9jtstYeAzqtgMIOVaOpvX1J/2DDCZS\n7YVUc+kDPVGjO5+xnwQCCRYEHrWXEyAa4/fPr0WtDP93JpZFGgfwx5gGXOmQ2BCZAU4Hm1ch\nfcTqoiP04Zd63p+zXwaqZEY5iKegRsPQO7/zfgpJIukfnqd99oK4j3iD/SUDoBvbKXKA1Q0G\nUrB66GWMfYiv/hyg3TYxS+JFaxR/5qtvsd8/G/kwSWxwUsXEhj383X3ZaRBfsUHQlV+9Zw+v\n846HSdFaXYUjndggq7XYE9SL4qBXJgNgCOENS9DopyEnRViRfBOWny22QqdvK4Bg9dBucuYR\nvAWwlomilbMtsQEzuzRXF1UmsUFJIokNp0E1QyjOYoMAk7P8q45aLZbMSeqpnCtnQyc2TBUH\nv32mgagvMLAD1N31LG/gj2t8GfqSO6FOLurchftk5FzxzRx+EhcIpB7WFKM5Mr1DPsBTltjQ\nFkSi6P8ohkFig5JEEht8SeryQnEVGwTX8OOOH7DODEcBfokH7HrvTjS7W05/H2hb83tcMfQq\n6IeVblD7viJsd98DsA3nyt4jMhjd80qp722AYMHB8db9VINkCrziGty7EBtWWxPxVOcTJDYk\nPvxEf5PeKg5gfYr5oMq5Z1EqLvY/j6kTkfMBbrStEeXOR6284n08K2vGH4fPRBjDr3owbq4U\nN1gs5Gu+EE6SxbJ2kZUkpQ7UE+ZdoLv8wHjIijTj9SIqFhIbIjQ4F5JVOZTiLzZgFSF+CdPP\n1eCAOC6VhcYjHsQ84eMa25pLcIVMOXmpCI67wlxYM/GgC573watM/kAErV8WK0WleNGCQjjD\neydgiBjFHVYFEOUpGIkNKhJJbGBNoaHCoAqIDfhzJ7+G7+1qIO92UF1yBNGJDeLohxp7gmvE\nlG1Z4eY60Xh/2P2F1k0WcDGmZ0DpoPgDEUKpuLT0v3UYgfJeCn711EWIDfwbtiWaqK6RSWxQ\nkkhiA2uNv8U7qAJiA8656APQytVAiGNeCRuYXmxYIoPCpieIcjcyiUV/0fbE9tCXHLACKeVq\nXK5mrFDcdtFjNcA5LfxBh2ed8p70WwGaCLGhN5wnHKo+oc4MsWGWamV1ERtYZ2irsoi/2LCI\nH3Td+aWHq4FIfFpDc5+5Zncvl0HxRXAN3vtw7tfi4SDRtiFsd58EO+9jzoYW/EG/dfZsTD3A\nX2B8BEA9ITb8HPrdzdfWVA2j2osNC5DzFyjmc1UbsWGIv/JxVQNPmM7m/10/FESW1RhvAZE6\ngSX9fXVl/46f4HXMYtkoLnW6Oq4gMZ/WY36Zbh2uwS/P2Vnip1cLzLcn5wJP4sG++wMfznO9\nFecR1YttwJWOmUAaUm/0uHH1xynKHVQbsSF7nPIqI/5iQ8mEWuJQdS2UvRhbl8U4CDlBVaSk\nE9XGewE0GGR9B+EtJvCjwwXeQT5X3IvEr6fw9NT3En+8sKBFrcyADU4Gny0e4d38jeEV1AAH\n4/wHdQWhai82rOi5kbVWNVQbsUFNFRAbcJ41EhACim67PCQjbj+91qAVG9gzAJ2tLEHi2ykF\ni75bPIIr8vPCkxl9gmEjLq5+89rrDBNE4tVaKsu1SRYlV0pBT+bRB5iAdyMNx0lCTVSjOAPE\nhn03TmmpWl9txAY1VUBsYKyZOAYH+q+i37CfO/FrfJFvQtOJTmzAfF788G6CkxDetM7WAj+r\nPYHHve9YmNjACtsALBca3XD5fEsOOH7Pes7/O/d24fMevHVqGortSvHkTBAbyuberlpdbcQG\nF+IvNgSSh1hXqF/dGFpSbLdo3K3xodvda/g3B57R8YfLZHc1AjX5MBPXE4rdvR7gLUyPD6PF\nU18eq+NIwvcWNJC7sEDIgLehav7a0a5iLp6Tai82SMpbaIwww8XyyJYpEr7B2dj321rfFY2a\nSpRafH+bk4dzdwqtnKoAjQJteZ3Vt5gcSK6RJSTDQFynOGrL+tZmWY/ExNe+eOPXm5gA4tYY\nB1zZmAyk8hYaSyixoQq7kBME4CnxBNVwuDvYuPk8gPp1OikSDpd7EM2FpmBNF7L/rHa7mNDj\ndPHd1+wzNP2D30UnnUrfcUtfnA2+AJp8qTSqEm+pEpOBVKK4NCexoeLFhh3yIukR8UTMyr4j\n2IjpfG7K0p3ZacUGtu20qFi0kxXeDNCJP7LVZ74X6vqYQ2wQiBv+ZCnY4qyyXtDMtYMM8JPG\nfO/vUdpUf7HBUWis4L21grdStxexwu3KxQ8HXBpwsSXX7WXW4vBWr1a+yPnO20Hh9q0HNX18\n/62mj5NbTmr62HJE08fRLZo+jm/VbYdMG3evePo4Pmyz7NnNVuskgHM2ZGdp+ijckqvbjuNs\nLPf8UeEsfnk0nD9qH2x9GX5RxH5Uvh9iWtA08TR/y6k+0Mm1j2P+9Kvwmesw9une86JtR3Tb\nkaN5Pw5q+1AuzASSs9CYb98eQXoqv4z15SkXpwtdGnBxsMztZdai+EevVr4oyfd24Mv7sUjT\nx6mjmj58ubo+Dpdo+ig9pOmjNE/Xx3CQ2hg+HWMdjaOt1okA17LTR3TbkVem6eNQKcOSFrN9\nfNngYf6oi611S46PlRxWvQzFuLqbxNOyPN/yln9172PyzyzVZKerSWGObjtOlMT6fhTpjiv1\nIp6FxghDTBTHH6ZuyP5slBVIP7cErkcAHjTUDd4aPr5kOr88wl9Wr4joNad4gEd8Q4TMpn+2\n7iyzSmImkKIrNEZigyEXqQBjz8MCeKeaQCDTyJ9k230Av2c+M7vii0ZwEVak7OCbFHId5uWi\nFSyJuI9ZYuATYh1mbAZxFRuiKzRGYgMSu9jAsqeuYF1QMP4XBLFy5g8DeJId0CW+i0hssG5C\nAvgly2l7afi+U4sNbN8//QemLH3phVDA4Vl3g+ovNkRVaIxmNiCxz2xgmCCyO/T3f6RL7vju\nL7h5N+N30759Gg/amQ1sKx6h3UJiNBTHzIZwZOlLL7LFnU2q9IEWZ8LMBhdoZkPFz2wQO7IH\n9GVFA2yB1LSZyMXdCGA6K9B9vet39wn8OhksPNdWfv5od7dPux2FYmbeXHeDM2JmQ/nrIxEG\nuYafcMk77BoOq23F0vU8xsBepyhWlgq35xjzF44Qy80NtzKJZyCR2GDIBRr0gXbe9TEAAAr1\nSURBVEYHxHQ1fkl0qJcMpMsYew/gmmOmxAZM+AguE7ON7Ip0dL/Ew6BKvKVKzAVS+QuNkdiA\nGBAbcEfys7qVZ4njfCqT9e4AahbijKGFzJjYUCSSprZXGriIDUH0YsPhbxsneWYpr/5igysk\nNlSS2PD/APNkgU5+jfG4dW43s+glkdfSlNjAcG4Q9FQaGBAbDmQf29awtsfmktighMQGxJDY\ncBc/p5PR86o/nyPnxTkA/AA3JTZI2U5dTMCE2MCj+bDXl84ZITaoIbGhkhgFYJVZWYNzEM6T\n1b0m8pDSBWp56IlOjxh0WG2gBJHxHoShYT4M0E4GEibe+nzXCvH4oWcB+LeqKbFBpLCr6fI1\nXWV2RUUPQgkliPQigcSGl+RPPE2s7FZWotO7J0OSz5zYgAJ7a2W9FTNiw16NAYkNSkhsQAyJ\nDT4866o1Y9ur1oDKpkyvCTBwItRhBsWGQe4zeIyIDRoDEhuUkNiAGBIbMFUptA5Z3Rig429F\nXitjYsNj/uyqTgyJDZ6Q2EBUOHjD+eUha7qKszv3XMZRMBtA/XvhGQ+JDfEehKlhYprGPiGr\nZXm8Lsyg2LAYYFGMLgyMokINSGwI58wSG9ijgNms7PwbMxmLokbGxIY1AP92MSCxwRsSG7yo\nOmKDSNN4Z+j6KRhIS5lBsSF/wFA3xYDEBm9IbPCk6ogNf+JBMzJ0/QeYT+RjZlBs8IDEBm9I\nbEgQMG9jeHYGHlw1TE5sIFwhsSHegzA1TCwsOT6sYZ5185AxsaHKuyCxIRwSG/xEKDbsAHsF\nL8lSgBT8a0xs8IDEBm8iCiR+0O/+x0pVXJDYUFliw36wlXaxOFAL2uFfY2KDByQ2eBNRICWz\n1KbD77v4HWcLiQ2VJTaU1Fbcunou/EwYkNjgp2qLDcmsA/9cPdDJ2UJiQ6XRwyoiaae5KMRC\nVDymAqkj/zw6eaGzhcSGSnAhDXI+dH7YXgw3CIMzbFdU7CCUmAmkxl3bjmA7rwsXjRiJDZUn\nNijpCcPwD4kNAaq22MCOZaxjG1MVBxWJDZUlNij5ZqLQH0hsCFC1xQZJeSv2kdiAmBIbPA1I\nbPBTtcUGSXkr9hFEtaGiKvaVbNooSEs9UMpK9ysXJW4Nhha+mL2UVEIftB0mj4jK2A7loqIq\n9hVnfCH4Z+pe/j7uVS72HnJpwMXWU24vsxZHt3m18kXuTm8HJXu/y9H0kf1fTR+FWYWaPr7N\n1fSRl6Xp4+S3uu3YflDTx74dmj5Ksk5p+sg6qenjmO79KMgq0vSxc4+mj8Pfafoo3Z6rez+O\na/rI0fahXFRUxT4/h1M/cmXO9JnuPDfDoxGZ8XxUBrNsj5/3GgAyTWcw8zmdwfPa7bBczNIZ\nuKMd5rRpOhcefciBxf5+6PfVdN0wQw1Ue8xtd8/SGQT7mLXKnbWuB/O7FVyxr/R7d0YMn+pO\nn8c8GpEH/k9jMGaAxmDqwPs0BneM1BhM6jNZY9H/EY3B2F9rDCZcrzGYOuRujcGwuzQGf+7z\nuMbi+vEag4du0hg82WeKxmL4YI3ByNs1BlP7PaoxGPCwxuB3d6x1J8P9aN5vIpDcK/Z5cc0t\naa58BDPdGwUPtdYYTPiJxiCt0wiNQbfBGoOlsExjcf4TGoMpZ2sMnq+hMUjrfbPG4Ia+GoP3\n4K8ai1p/0RiMba4xWAgrNRa39dQYDOmmMUg79ymNQdPxGoORl3o0/lC+I9xOjBX7vKBAQiiQ\nAlAguVfs84ICCaFACkCBFB0USAgFUgAKJERdaMwLCiSEAikABRJCgaSEAskPBVJklD8D5y9v\ndR/xR0mzNRs8po3G4PFmGoO0ziM1BlfcqTH4B7ymsWjypMbgmfoag+m1NAZp13p8Ign63aAx\neD9prsaizjSNwfiWGoNFsEpjMaiXxmBod41BWsOnNQYpj2sMRnX0aCyvDGCjAq+RNr67ITNj\nY2ZGZnoGJ50/yMjk/8TKzPmfZ6anp+MqfMZN0jMzhS03zkTbdUv5nw2Z6ZYDy1Y6ELbrFwds\n0YHCdvmHVme8VXSW7n9mDWzFe86B+W3FwDLmbXAMLLSzV9Y7BpYeYvvpQpeN8Hf22d+dAwvd\nY6+/4xhY6B5bvdo5sHR7Z3w7HAML3WPz/63cC8GBrV/s9lZathnzFG9lhr2z91Y5Bxayx95f\n4fZW+jt75VOXt9I/sMXrXd5K/8DSlgUHlmHvjK/+Sjd/3YMKDCSCOHOgQCIIA1AgEYQBKJAI\nwgAUSARhAAokgjBArIHke7ZdyvM4rbX9P/mzLwfyxYddUl60WsVzaxmwbZycnKxNMuDq3vf7\nlFZLZKNcG3RnH4SXi7JxLS/5IFoXoe4idaHwELSIdhB+RzG4KL7rgpYvxbgdbMiCGHdm+Eui\ncBE86CJzYZxYA+nrLvn7W23ae+Gxby8qYU9fyEd7vHX24aYHRaN4bi0Dtse6xuT+k875+xqK\nhCJybdCd3crTxfLeuVnNT0fpIsRdxC6cHoIWUQ/CchSLi9duKdt9Vn5M28FW1FsQ23aEvyQK\nF8GDLkIXxok1kNa8wNjQN/4+mLEOmezdp/lolzzAWI7MeyOeW8uAbUbbjh1fj979pk7Hf6gv\nci7JtUF3ditPF2NnMParj6N0EeIuYhdOD0GLqAdhOYrFxbbv2P4LimLajn1Xj14Q23aEvyQK\nF8GDLkIXxjFwjfT1BUcn/5Gx295mLI2P9pmhV18612pKGxhc+m3XDc/PalqOuRhh7tnd9ZKm\niwa5NuguxMrLxaLeORvrvha1i5DHkbsI8xC0iHoQgWUsLh6Av5VvFGEeym7cOG5BbNsR/pIo\nXAQPushdmCXmQCr5c9uNbNIzfLRvyNE+0X7Xrlb/eaEbznINBpJ4LmyR4f+I2v07PQ9t73oA\n3fnXojv78/Bd5nBROrbdjX1XR+vC9rgcLhwegrsl6kHIZWwuGPu+aXYs2zH3acYDKdZBhL2k\n3C6CB12kLkwTayAV//rePMbmDWWsU7oc7exx/FtjkWwN/UaStht3MnbfyqjdPzqLsWEiDuXa\noDu7laeL/FzGev0nSheh7iJ14fQQtIh6EH5HMbiYv56xm96JZTtub9m6/vmzYhpE+EuicBE8\n6CJ0YZxYA+nVwbjMbnvqh9YlcrTbO+Tva/W1bA0NJGmb2ufkgXYHo3b/yrXH97TICK4NurNb\nebpIu7Igo5MvSheh7iJ14fQQtIh6EH5HMbhYeGtZTuMfYtsOZp3aRT2I8JdE4SJ40EXowjix\nBtLomsnJyalsXucuePUuRvvCJa3891yEBpK0LR3XpsOa6N2XPty85UzZKNba3NkH4eXC92Dz\nq7ZF6yLUXaQuFB6CFtEOwu8oBhelo9q3XxLjdvgDKfpBhL0kmvcjeNBF5sI49IMsQRiAAokg\nDECBRBAGoEAiCANQIBGEASiQCMIAFEgEYQAKJIIwAAUSQRiAAokgDECBRBAGoEAiCANQIBGE\nASiQCMIAFEgEYQAKJIIwAAUSQRiAAokgDECBRBAGoEAiCANQIBGEASiQCMIAFEgEYQAKJIIw\nAAUSQRiAAokgDECBRBAGoEAiCANQIBGEASiQCMIAFEgEYQAKJIIwAAUSQRiAAokgDECBRBAG\noEAiCANQIBGEASiQCMIAFEgEYQAKJIIwAAUSQRiAAokgDECBRBAGoEAiCANQIBGEASiQCMIA\nFEgEYQAKJIIwAAUSQRiAAokgDECBRBAGoEAiCANQIBGEASiQCMIAFEgEYQAKJIIwwP8A7CiD\nAOdlsykAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PerformanceAnalytics::charts.PerformanceSummary(emh::as_returns(gbm_walk))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  |                                                                            \r",
      "  |                                                                      |   0%\r",
      "  |                                                                            \r",
      "  |===                                                                   |   4%\r",
      "  |                                                                            \r",
      "  |=====                                                                 |   8%\r",
      "  |                                                                            \r",
      "  |========                                                              |  12%\r",
      "  |                                                                            \r",
      "  |===========                                                           |  15%\r",
      "  |                                                                            \r",
      "  |=============                                                         |  19%\r",
      "  |                                                                            \r",
      "  |================                                                      |  23%\r",
      "  |                                                                            \r",
      "  |===================                                                   |  27%\r",
      "  |                                                                            \r",
      "  |======================                                                |  31%\r",
      "  |                                                                            \r",
      "  |========================                                              |  35%\r",
      "  |                                                                            \r",
      "  |===========================                                           |  38%\r",
      "  |                                                                            \r",
      "  |==============================                                        |  42%\r",
      "  |                                                                            \r",
      "  |================================                                      |  46%\r",
      "  |                                                                            \r",
      "  |===================================                                   |  50%\r",
      "  |                                                                            \r",
      "  |======================================                                |  54%\r",
      "  |                                                                            \r",
      "  |========================================                              |  58%\r",
      "  |                                                                            \r",
      "  |===========================================                           |  62%\r",
      "  |                                                                            \r",
      "  |==============================================                        |  65%\r",
      "  |                                                                            \r",
      "  |================================================                      |  69%\r",
      "  |                                                                            \r",
      "  |===================================================                   |  73%\r",
      "  |                                                                            \r",
      "  |======================================================                |  77%\r",
      "  |                                                                            \r",
      "  |=========================================================             |  81%\r",
      "  |                                                                            \r",
      "  |===========================================================           |  85%\r",
      "  |                                                                            \r",
      "  |==============================================================        |  88%\r",
      "  |                                                                            \r",
      "  |=================================================================     |  92%\r",
      "  |                                                                            \r",
      "  |===================================================================   |  96%\r",
      "  |                                                                            \r",
      "  |======================================================================| 100%"
     ]
    }
   ],
   "source": [
    "df_gbm_walk <- emh::is_random(gbm_walk, a = 0.9999,\n",
    "                              freqs1  = seq(1, 20),\n",
    "                              freqs2 = c(\"Mon\", \"Tue\", \"Wed\", \n",
    "                                         \"Thu\", \"Fri\", \"Week\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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e8OTexlz/iUUakVtHZeh/aFlLxV78g7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\nAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by frequency”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_frequency(df_gbm_walk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kXfl+S+SGCKfe/VqfdKT7m+/Csg5XVK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\nkAABhAQIICRAwP8HlXjvCAyFqukAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by test name”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_test_name(df_gbm_walk)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Benchmark 2, [Merton Jump Diffusion Model](https://en.wikipedia.org/wiki/Jump_diffusion)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The Merton Jump Diffusion Model is another popular stochastic process which combines the Geometric Brownian Motion process is a [Poisson Process](https://en.wikipedia.org/wiki/Poisson_point_process) which is used to add _discontinuities_ a.k.a jumps a.k.a stock market crashes to the time series through time,\n",
    "\n",
    "$d S_t = \\mu S_t dt + \\sigma S_t dW_t + d J_t$\n",
    "\n",
    "where $J_t$ is the jump component given by,\n",
    "\n",
    "$d J_t = S_t d \\big( \\sum^{N_t}_{i=0} (Y_i - 1) \\big)$\n",
    "\n",
    "where $N_t$ is the Poisson process with rate $\\lambda$ and $Y_i$ is a random variable which follows a log-normal distribution. The R code for simualting Jump Diffusion process is also included in the emh package. In later versions I will include calibrators as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "jump_walk <- emh::simulate_merton_model(drift = 0.1, n = 3780, \n",
    "                                        jlambda = 0.4)\n",
    "jump_walk <- emh::as_levels(zoo::zoo(jump_walk, dates))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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YStw87qWewRvInL/yDOAubvAWo3tSUcnQRDHIVQHGjnfgYkALliNNeVhqOEeC6C\nbac0ZK9ZZAM5/01xrsYRmmzwgi/ZUAuXdvL2yNJkgwkb2aAE5r4SgtK4/Hs5Mr+tgmpkJoBt\nSMkdQNW9onJYRKmZn9uuGpSnzVITYJsSTwMy3N/AHdBdLGNd7+ItcZjYNzwyluxqdqE1yAZy\nR3/L5xfZEa8h7X7lUUICNSsUbbJhfSkMP9lb/FuTDSZsZIPy5/6aXkTA2kHAOeVkq9Jffsm0\n7fA2FVLBXs1pcTnLPCgjhPUoUutWnCaF/j7yrBza4v7ya48eIpsZwPLnoQF38r6xbR4CvGeR\nDSRNOd25GkfEa0jnlO/dTyKBmhWK9hjpLTkY7ubVK9dwxM1sC9+qPGKfVwBalMRNbCZVbaVm\nUCGlvNqeFtdxupVyypAsMeHHuYXZxazDH0ZD54LjiBdiJ7rql6G2uEB1Ly2ci+LhVpWY+Q8T\n+EnxGlIZ336SM4qoIc25h99b8iaOORUnpvpsCh2Gsi3ME4J8wC+V/xtl4laKEoqYSmCPPBUS\n3psWs4WlzmWTt1ct1BpmMNgpz92x51iaZCInOtQbhuqC1Fdm2DafhuPCX/YUM5Kpx4l4Dam1\nb4onZxRNsmFvJdXluAN48DTvdBSabDBhIxsG8MO/QGWYIMe3WmkYI0gqy+63yKT3BF7kgU2e\nSqmkMMYs9SB/lQd/gmXvo1WQ7WiDs8SKj6hM02tQmTKXRYSut2P+1SAbRIvI5soP8RrSx4N+\n371nj9/DHYuiSTZkGR4mI4FJvbx4Ik02hGEjG5QS14/KC+hMGrMA41h6dbBth/lUSGmdPiqX\nSgjxa9iQbjFLqfFWFjdNT9Ciu9DCkegnlnGHsdX1KC/owOPFeusFUIPDJgyygQj52T6/yI54\nDalCBp9vAjUrFE2y4TfgGvo7DCWWn+md10WTDSZsZEM/fph+kY+fbJu6g1VQxvPg3x649xOQ\n2Uj1O54CZ5FYFzYkK3PvvWZd96teokfaFnIez+Z2rt2NKCV6yoWbsytnmhS4CpA1yAbZDzT8\naeNDvIY0fdUmQgI1KxTNMdKPlCBhabUuF6Kh6IPMgmatP+TQhx/+RYKFGToqy3iIJ2DtHnBL\nYA0/abKogjDUVhmWusI4s5t4t+zVAc1tvuDRaIaBhoJaR4rPIAseIQ/yurG5WLiZE8xveOqs\nRSFeQ6rjV84FRdOQzpYvP+qTn4gjqKc9J9XnU9hwBkqnq6DwGaR6xXiM2xZ7WN5ymKkoxQtQ\nGustLEOywo7u5K+y8RgD1AB6oazrYRvjQiNK8AaKGDxBLgyTvcWX1dYQcKetcCeaAY4f8RrS\n+11/3p2b69dNiUXRJBtqU2devgGb4Mi8c4DPParQZIMJG9nQE8dL06BB1afAUcoynmLaYIxt\nhzVhBu4VUBiR+K+DZUiWZ/Yd/PUrYcjfnYPirmfQABeLFXNloYdDsh3bST7gQ36wUk7sUZNW\nJtlwCvcX40a8hlSlePBjpMJLNlQB+tPYuCSOyTnfW/5Tkw0mbGTDqThxLsrSlZkJNFOW8QzP\nCNnFNrcCZxqLRLXVli+ELpYhDTFLKZefT8Q/1XjhItnUzK02RDihLoaKZRRolE004G9UfOB8\nYJLami0NTITJhp7MYMSNeA3pX4UEalYommRDOaAvT3uga2iCd/IPTTaYsJEN5Ib9PQdMzAbq\nK8t4kZ197L4zuWHfn/zHaxCJsPdsy5CsoLtR/PWaze+r9dcCObcg01G4mCSJsxfLQnto0MXx\n7n2/tbyNNlKrGCYbzgISGfvGa0ivKiRQs0LRHCMVp7z2F9GNOIu8Gyf776FhR2dyw2bMJdEL\nQvoq8iEN+6ISStlEs9qiMRU/+TzDkM43N1yLTPpe72S1/lZg1w2st/rph/Lxm2Z/V7IksRx5\nIY9CBTkwqedsSwZ8baQC0YWJ5dmM15C6devWtUmJCxOoWaFIGlIoDSizlW/pReRL4pCEWsML\nYY95a4q1DGdubRXBC3ezpR1rb+TqnWaUt7zVrkRFhFH+YWDrddSY/J6GbhuqRmR7rkyTFpvS\nSZnoK6N8ly9Uh04wSfiGrfBVpE0ZPxLx/g49mbg4b5EkG/bSLfiC5vNwR16oZHhOwwGabJDj\n3cmksGAjG9pbcayW008Vdt6JFFLYa+tbdcQRQvy3hgqVpTwvfYz1qy9EnfSwITV5RDYkV5OG\nCiVNJ9bc9sPK4zqxYns7oiMWGOWP+8Ry25uthMdNsuFWpPv1Zu1IKIxib+0EalYokmQDe/K/\ndwp93p2jkoG4QpMNNDah7LSQHzoAACAASURBVOA2suFYnG4srTEtoI4QS2XHzLWOrhRAtH4l\nTeGd0BKWU9402TloWCZsSM0fB/4ZRn5878lvdyKiWSkjX3nLtnal1m+JUb7Vh8A9ausHiu82\nyYbvKg70+cURSKhFmuw+1+WGIkk2cJzZFKZiJ4VEowi/lmhosoEmaChgPEw2TA7TcZvpIhIj\nfJgc5pdyTLai0IMcSPbuFOvTcP5gWNIM5FbU9OqwIbV9AVh5GWkTkcAK+cTaLm8J3Cyyc8+h\nqd3VRvnD3gXu2nba4DxWWCG+e5/fG8MZcXt/S5T0+J1uKJJjpL/pFjzPE4lTKan8Oak+oYMb\n+2xkNeOqsGTcLrqIdemZl1+mXu3e1x6AbmrhpVvXXyvLd7OqwhF7wobU8Q1g6RDq+T1rrLGN\nutJZ3GEYzUjlVVZb674F3D6dQ87fVr4W+4l4DWk5wS/w2gFF0pA47OWJNvT5ruGcr+GOXTRZ\nYMfQMHudRxexE9DoS59KVt8RntWhqaPOavESudgmL2xIp3wGfHshUHvvDcaa8PDwexV8MbcZ\npXRpqrZWlw3X6De4U/dmYhNHUYjXkKbx59sJ118kyQZ2Qr6HeuqYkCdOMt+OjtBkA810nibs\nZMMg4BVzY6ZsFb4x9FE3+o31/lNjPXKv66DWUFRtO5FhGVKXOcADA4Bqvc014eHhm5Snb4Ux\nIuC71w4VXpL9zleA71ggj27Flv3znIzPkObNqzpP4vNybqXW7RU/vPSrw4YiSTaw3+PN/E57\nNUecHkGxRkOTDTRBQI99mGzoZ9N3LCPHmVnkuiixzikxkB3rV/KfOSVBulwEcn9tL0qGW6T1\npXG8XFmxvrlmpbX366Rbt8wYcdLwCT1QahJw1QscMfEyQO/mTb7vX0fEZ0gNGqQ3ILjxvE/V\n2PRE/YvrPx27pUiSDV/TTRhELikZm0PiIjTwqEKTDaRbn7bVTjb0QhPrqsixyswVRvjEHj9r\n3mu8XXdbLy/KV9ZJlLMMaXyetKCaQJlq5pqw4uTV5A2UbRyZg9fPQvpTwGXPsLvkAwAZcpLJ\nhu6ehWpuEIf/JdY0iN1SJMdINEUBnrwoI0iAoJhfv+jQBlHcC+wr7DIXtYDv13vmkHDCWTSr\nJN+E99YDebYq5qBRpYqTSbMTZWFDuME/DXjJ+tKFtg2U/UBgsDSmjwS58fu17B6I15BC04b1\n/ftNt9TrrdaI9ivFDofYxCJpSJ9ad4lc+1/kQGcNV6wEh3S/95XZLp5okwI8XHa+8jISTR96\nDtKoFb6Pb0IPkvwGOTtQayMtJNNuSOH0FifbI8uZixjKvucnPUqk0Y5WXgJEvojXkJ6pNLry\n2moPuRT6tMHwQYePbDEhdkuRJBtmGPeoacbApXmUWmGJYzGGJhvYu+0p6g9XNU7jGGsaiQLE\n64XE0ewuGjfZwByDvHchVsLDGZSEorLycF2+c4BlQuX58ydr7xNJENkkG0Lk/D1eFbweeJPD\nMeh2J5VsEOL4WaKG+NY1infLy+NueczpiSiSZIPhaIzbd+1blENT6D+6V6HJBvJYwMM8QWoE\nbtnzheVNl++7TbO5rxMv2cDqwv8aog7kONyIsyuR4kJW9quWIalIpXDU5bG0k0k2iHw5cjM8\n/XqT3zHlvqBtSSUbhCiXLQ1pSxnPoiGHcXWRJBumkeQtqGMd2hKijt537lVoskEsBMUZkdi9\nSuEiGrr4gsRNNlBlPbabSZrPpcDZ54Gr5IZteb9ZhvRSFfoMC24dSf7c2db9yET5fYqlaEp0\nHumw0MsiyWRD1/tCNcRjnTyLZtncifZ8MJ3xztSsfWJvVtH6mAKUoBvwIn99BfjsYDirg/aD\n4oxuy6L2YQKve6c0hhawUnkH5LDmPWUwvfa1RfrjwHW89SPLkF4jSg8PG7vtuExazTpbLSVR\ne29js+ydWafKz5/3/6ziNaSldVsUP6KGd+xtrs0bI/TP34z5U7NDIpRdtD5eN/rfH/PXmbRw\nEJzVQftBEkC3ZBMx8BqvO0c+twWslIIpjllsGNKAUGdUeEsaK2/9ybSNzPUL6XX3hLEbSxVv\ntdVSHs1CrczCN2b3ANI37/9Zxe20uuvdx9527yvlLnh/2nynTkyRJBsouzxd/XkidymrFr7n\nXoUmG1iLYRRrPCpV+m6W3kgU4icbuNm5+h1lBNeK09HwC+XFvXznStM2jhHi/Ayw47n8gSPY\nZrZbZAP5pB8tjjcLX0kzUpx6MclkgzdmNm7Rt2/LhrNitxRFsmFfhhEf/aMgsmGxZ9oCTTaw\nKkmHPXfCFL5qEylwGkb8ZAPH5V3ypjKCB8RQdJqjtBeysq3ADNLH32SKh/+u1u0Kkw3iDPQS\nnc3CF9IM7W20OqlkQ94LN80Wf0172E3luhl7+61sHbulKJIN56rxKXmUENnwB6XV+fM9l/PV\nZIO4nq7Ve2ROqiE6zE1VO36ygfgLDDIIuhfFhvF//KRohW15/xqmkU7PR44pEm7wc3ttZMOa\nu1fSHK3C2eJoEnsVSSYbbijdtcbTJeodf5FLoUbcR9p5ZOyWojghW1te+CMBU1BgFd3KuqYW\njUYMOBfsKyRSooSvakdmU9kfZFGV572kjICzr+RdNkC9LbYYpqGcJzJUM6MsLyL7EuN205C6\nUeaYxwtwRvEZUq0Z4js85ObXIMSkRgPHjhvU+JnYLUXRkGh81BaW+sw64Jl8I0ejhgOupCf1\nOYq+ky+bnHNPL4uMgmrT/kNV9iG1lKMjs+7JBtxwBT+Lv5U2otenqpXRzepzpiG1FA2BxLV9\nbGcUlyHhX5Fbwku3bM2kMXdMdOrhFkWygTy7OqvHgsiG/4An9smhr3MVmmwQl9OT+tT/1Ktn\nIH1xuVbxkw07qZaexKuPfCdigLp8pzDcVdUxqigvvhlqwihN2MgGwgdAMXbUqyhqGtknkko2\nUJhhhZX7U39RJBsqyH7D49w3Z7JhO/DwTiMQIBaabODgOzw0RH5035jH4lt3OReMn2ygMCZ0\no+QTUb2grGwOmoUpP2zM/RqkQqawkQ2EXKAha29gWxl05Y5fUsmG5BhSYSUbypDczOscnEZk\nA0ndbgMGOFehyQZBEgtoS/nxcDv3yeDisxk/2cDNzkn3A6dFnda2PBXkAjzC31upoPZKat2p\nwkY2MErjKuWw9x55NxCSSjbgzgcfLDH6wQe1ZgOhJNJC5G9nJL0OFcdN/0Hn7XMF9+aqcADQ\nZcv5qZ1Y4DrvLSvbku7Kvy4K3ymjUVKTJ7J8+D616ozYl8Gz5665xBwnJZLEPAbxGVIHEwnX\nXxQNKZOiJ2YAZuB9E/T/F57RfYc2WEmTnRNxDtNt4UDzAlWa3hwlHdK8LiRNdjOV7HnIfFUl\nhJWn4Dx7dSPSVdyFx7S6P4KZkHVHUSQb0khd6jOmXYlsEG3QZw0LszlBkw3vNYKFbsql1OWh\ni59s4BTkKBGRKZOxfKf4BahenGSJCSM5m6bydqhEK1bEjAi+KXs+Z6vFZ/w1pZ4N7iiCZMM6\nYKwQX3JUJZENlCxb3qmazlUc8mRDqHTYjtBWecJ97Fw0AbJB/HYcVRSj4ZiVTXNMjSrCCFQY\nw44/KmUmy5sucxpxzuPtanIryWEU+4siSDa0Au5lgdtPFdkgOuCUPyIT29twyJMNu2x2hGas\nG+OW5TgBskGId6mimHCMbXkkht+mttlWPcgKRpzJnDQoY8gGBeVApKLKkhxGsb8oemMk0it+\nQL7Z0tLMIOaT0Xmp0XHQiMFiuyHVfJT/fB1AvRymfInDhmyg87kmnzGRk5W9xkdt6VrXBt7u\n90bzhDakRPEIVP6CmZai1KloL7v+rlJlhzgooC8dkfAIhIwbPK5xUl3Pz0C/PLOTOIV9hZ7n\nox7nWtdu2pxRoNMJRvzEHUWPbBgOm1MWkw290PZHoLRzFYc62ZBPY5k7Tok0pIXOVSRCNqjp\nohjxoeWy8zekRji8/FO2H3KYPfsw9vSLJRuEytODUmo5yWSDt/iJO4oe2XAhEE7bw2TD2Wg9\nH26pSw91soFnYGexz2i4XXKSEhWJkQ2KIIgRH8qKGqnJMVlr5WasODlnsoEVJiuoxSSTDT7i\nJ64ocmTDZ62AG3PMb0w2nIcWc1x7Boc62fAnPe9LmPXuYRmSy7sjIbLhR6poVHSJbXmR3+UI\nrQX7olQ0Wm1HskFQrrLqajHJZEM84idOKGpjpL/ptRqVNv4CNKFAs5UpOaGDHZSIKG075xP7\ntK9pSMv99/MFkxi+LvcrgfoiPw1p3r34mrKuugU6nSDFT5xQ1AyJ34NRMnaD0Yj0bPzyKRya\n+AkocTvFbCFtycOmIf0dQMUrqKK7/UptIBHPHfIcvIs1Mtnx/UaQ4idOKGpkA82DVAk3/kw2\nDEH9D8Hzsw441MmG70DqwhS2euvSJw07OirPsWhiZAOFlB8bM4ZdHjW0ljZUko5+lLnCkWyg\n6HfqAhKS7dngLX7iiqJGNsyVV9yWV4zJhqEoQRLUzjlvDnWyYRbTZhS2OmnRglLKkEa7VJEQ\n2bDJsaJosiFUC8jNsnn3OZMN3cK3Nclkw7eJM9+MokM2bL/0AaFIV1tudyYb/qceD2dlnEOd\nbPiAGQHKqffyFtFdXamxLlUkRDbItsaIObIjmmwQshVc+xDwvvndmWy4LMwAJplsKNX03rX7\nU38RGSM93mLmK6yxTokoLovaeKV6PBwC7TXEnZzjIZRO8tqil7pSDwRRcQ7YVcsPstP9XinO\nf+SF/8bBMze9P+I1pB1Tepc67a3E05cUEUNqikETgN9VIoprojYauYAfc9v5k6MCCBsohPiq\nxnVCnI+a1Jkpwy7fpL9UzpSaKyiqKw8TH/wqW0Qgc7NPMdlRvKVAZ5OAi9DWF5sm7k9WRMiG\nuuh7J3k15g+Vj8JN4QJMNoxQhjTOsYrlO0QftPE4RtElG4ZR3NZZYJG2qrJ3tTSf3Hpa2LMU\nRSIhskF8Y8nP2BBNNhDRcAFJMphwJhvEVqufmGyyIfTzbc0rOPkIeqOIkA3VWOz7G+XgZVMc\nYLJhpDKkzE+dqsjaJo5HLY9jFF2yoT/FMvRULm7NgY8X5YqyQL8hHd3SECVENohQl2qxly6a\nbBDbgNNhuwHOZAOpqRj9xCSTDTc0LnXe9P1ITFdEyAaVaucT8URUF5/JhhsNVvcmpyq25f7o\n6j7EKLpkw2koRrkpO9LyvXKYItv/uzNwh3sVCZENzoghG/YB7YHG1ndnskGEDkszpi+STDb0\nem3/6i8iYyROPoH3xVj6E604MNowJJf0jcRP+D2FRRJt6Hd3UNn5JpJSusSkS5zl1JOHTOpM\ntvAtttWvY+ADHUYRD0JKceAdngHPiM7Pd5thSBeLvU6vu0/kJr8moygivxwwX7RFL/ryoj11\n3gFFOVSE5yA1GMRnSBmTMxQSrr9okA17DdqWU8TZPRiYbBhjGNK5f1asFdPLX76D8vt59DKL\nLNlAbkGvipZqonMK8NtSv3Y5MbLBETFkg+AsFOFQJBeyIYykkg0rd6xRSLj+okE2bIcN9oeS\nyQbu71Vshx6vOUg6ZW17W27dFL06jCJLNvwif/dD+dWVYtaqqkdsW+Q3N50Y2eCIGLJBjWA7\nWl9dyIYwkkw2TONPZy8YLxwosuHv2K53gGTDZrsh2ackmGy4h9bW74l2T1Mu0ihsy6XkqR5P\nOpMNXu1BYSUbriCCczZwo9ocCvm1/0khG1THu5v11YVsCCOpZMO8eVXnSXyeeDj1ARojzStW\nza/JLgg22A0p5mY+QGtbXoAm95qyhFNn2DZPllt9ugsXZk4P8nQPClAWKdz2AvB8as/jLro7\npyf9MPEZUoMG6Q0IiXtRHCBDGh0T2xAo1toNKSd6K0etdfofat4KTKAVc5FuG8A9K7f6dEMr\nY1iwJ3wQgJxKceMEdqxKJe6l8+ib9MPE27Xrzp+Ju38fILLhalNMyYYAyYaVNjtKtxdgskGQ\nctst16JkNeAc8kh8E5hrlli+4ya51WOYQ2RDKQxxL1BIyYbVdLFGPAqYPdPc1JANlHizxBvW\n19SSDTQanTNnzmdVvEo+6rTyAJENlzq03gGSDX/YDKmkvQCTDZR3Hs/crDafKli0ZqZZIovY\n76gUPhHYvpRcOmOUDsMopGQDhcbiyvsB0wL3poZseCyyQUo12XBrZtlKdUiq1xHPESo/91zs\nlgNENgwEMqItL0CyYYnNkCLcfZhsEE8BXTffpTY3ld/la/gDs8Q2zmXlIptDyNtGQQb93AsU\nUrKB9U6GjjW1g+la+Z1EUsiGp+VpDAp/TS3ZIESNr368JPSIm4rQwFJXjhxZbuTI2C0HaIxE\nqTmSOOH3i82Q2sdufhGYoygHJbgqn57wz6auhY+Q21bgjIDPOPX4ln73RbdSTqKUgl5klyf/\nMPEaUomt+e1FrqunxZsdFooGThsOkCFRUl1Hn9FgQAHm15ZUltI9dvPCjGo7hRFHXUyIDRXs\nNPg5tNY7Z+o6x1oLOWbR7+4/AokL5gSLjxAb+JIExGtIrSaE2v/1XwXXYmtPv8tRheUAkQ0k\nQDgtqkDByYbNJw3gDs3uxrL6RyooS+ljL6HIBvHXJkXOKVLvS9gc/JeTppqXMMquP/ZOATxk\nZQop2cCZks/sjlbmihSRDaFS5lQWI9Vkw/Tiyx+rUtslKx0h/8nznFYfILKhC2KT7hScbJhi\n8NYL6Jl4yshNGnENFNnAeMUwpO20G+4xV2fxbp+5H2T70sucO4wmCifZ8HMapSnqcgKzL4wU\nkQ2kWWfzOE812SB25OTPeNn7tRVyuFAHiGzo4NB+F5xseJpI9bXXzOLEB8/VVYYSEZOlyAbG\nW4Yh/UvcA5qYq7eR9qCLwhAjb1tHWaCde4HCSTaQY1QdHNs63IKniGygSNp7wt9STTbEgyxb\n2X1zZjNmTF2VK3JWJfuDBKZbBV7zvcBbucPQkCwDz3O+rIq41aXwB4YhPZ17H0j/1txQBtzt\n9DhQa1mg5QG5TAfw42X6UTisEfqn+lzkC/C25B8ozhyyJjyL5tpcM/MW/8r4auqGfJG3Ptkf\nx9JtC7zm4cAb+SejgmyZij/4b1se7Dy9zaXw58YlejT/VpCkvrFhHnnK4C2vAx0hC7Q4IJfp\nAH4QWXYc6lTEJak+FznAHZ/8A8VnSGvW+Hh/5y54f9p8p0YzWLLhuXJWHohIsoFf6lGFC0w2\nPMBNSRsUexGoLMQLZBFRvrEG2UCYbRjSU+Ia+vOmsfomRfX1cHUS2vXH4fCMPCucZMME+aNO\npsyxls59isgGinK3DVFTTTa8quBSaGbjFn37tmw4K3ZLsGRDV1vu8AiygV7qzaMKF5hsqC8r\nfW1GKeBJnuehuKLowCIb2TDXMKQhnN4UY4zVg4zVbqKIYvvSBlDzuC4onGQDxZaw+pb1zKSK\nbOgd4eqYarKhW7duXZuUuNClULMs+lzZOnZLsGTDMWhrLdvJBupMhcf3BgpKNuTyyEjeBtzF\nQUh/kk5o1PNmIxsWGhbT8jemF0z/3nON1a5TGXnbSMG9nvt5FEqyIbcsUImVMy1pxlSRDddE\n5Dc4GMiG0JM3uhRqxNdo55GxW4KdkD3MJWaYenZoFOSRBOvPyMaIxEEHA/QD11dBmvvjZHk/\n1ONPU8ChhbH2CvcDVabts4I89dSDLt4119MPc8kXe+AwCtgvbdPEkBBrt7e2S6FJjQaOHTeo\nsYPWaLCGVB0OtiqMp9Xjpb5f4BRZD3bivj74NVXPa5qe0ow0slgZ052b1B44m4mHkhlLFD3u\nvr0wYqP8SXfz+HCuf+HkYjTgN4YMAAm1SJOruZVaM2nMHROderjBkg0Vcbi1bCcbDqM7Fi0e\nV1CygV2+xx7PNC54LN4ENaLK2MgGKt7WsKLSliT7XhpeFSNjdDvMrj9K89m7tnWFkmygCK6n\nODjVihNLFdkwRvUnDKSabCgjURIPJlx/sGRDGVsSGzvZwL2p6lGFC0o2/EqV3kIJPzIMPa02\nMeMwG9lAMUs3ZypDkn2a+q2vpLXZJIPXXq5Kc5Ov2760OO/j2v1IDtkwrvFXtm+Bkw1/0eiI\nHeKta5wqsuEeoz+hkGqyYTlhPyTJAiUbcjIRTr5pJxtouE4MdQQKSjawY9D1aoyj7PeVktH6\n0Daygd7Bc/85lUqnPc6f9PM2kNsdq+yvyV/i+EbO26Zyq37rdh7JIRuqoYNaUNcgaLLhd+Cq\n/In0uyzrSRXZ8Dqq28495WRDzlZCwvUHOka6FXAepcnhehrcPWr3D3PoMRjWmJ/yHv7FSdch\nS/Sj0s05BonnnP4mzQKO+ftrmEs4V75qxV4K9OT9kJOGmrzwdcnTklH/b6QCSE7zXiKzBwah\nj4PItOmHeA3poWJ8txOuP1BDahrbf1MoA1QL3F//S+YMFAd3rn9x4qn+FedT6RN/4ZAL6k/9\nQSnQWTZgWWWc5LjjPmVIwaRoiBdEBvCg5g5bmxEg5lJs48+wy9cXbcRrSBWe3LJDIuH6gyQb\naGInnA8jTDbkt5PDmL6RMeCi4GTDx/R496/FT/nFLmVsZAPZwx5xAZhYeJT+0CDuV3ozc4TF\nZ5nO3P2uX5UhPeJ2HkkhG2jS+HtauIFHEMGQDX9+bX2bSLw3BRaHuxCpIhsikWqyoZ5fVLYL\ngiQbdsr7EhYEC5MN6+T6kbGhmAUlG6ZTf/Gs6vyUu4VY2sgGkUlv34uo9GmCtOxAGXfnkH8K\na6cUj50yZmyXYzE6yP1u55EUsoE8AD+nhatZvTIQsmFPRVgyZA9Tz3a5PEgzq0CqyIZIpJps\neOjyPwJvkRIlGygRaaY1uA+TDXS/7hmDtKjiBSUbpgJlcDrPluJqlzI2skGUI42NS6l0HzW+\nek6MPewmEo//z2DFazpVkTcfuPFIjwTdySAbuDv5Di1dprqgQZANa4HSZijwPcA+5l/CE9Gp\nIhsikWqyYQJSP0ZaT2fg0IpR3+gBm8pGQJhETgqnqLhYBzWKGNTAYEquJXGeyCce/FZRHaVo\nImWv4uVQ1nG/i4jYS7Oc8w4ItitDF+wLGNBY/AuaD7vd+HIbMuQroDr58B4aiFv85PGNKWft\n/rZeo5H4Tq5+7F5j0jQ43IzindGJw4ncXU5t6E3x5ez1N4Qz1GFYPodQyAFMA2VI6Y4ZrU8F\nJoliBcy8mCBYvZFnBc8BFgVT57WqMVYYxdyP7OG+4bVLEUK8htQ4CWOkRMkG6sKFA8rDZAMl\nIJrwADAxsuEvKNkwHFW64AQleRKbPlvBRjaIfTRoY5bhZsqVCQzlLl2m7BNNOUZZktOAfVdL\nIvZKu+cCTgbZwNKx1en10Ju1woIgG5j5NwWdr6K0l2J9aVsOHE02EJ4f9tceiYTrD5JsYHW5\nSea3MNkwQ65+Xo5uEelTW1CyoT/qdcMxylfBLX22nWxg/FpOduMeYqYeF6+hXUmfix3x4JyU\nYnt9EkCqgBFu55EMsuFPdT5/UWpKkjgKgGxYexxXqSbtvz5cTZ2vtN0DTTYQKiRhjJQo2fAD\nnYHl3BkmG6bL1S+TM0GPiAoLSDZkZ6BZHxypUoy5CfrZyQaFfdezhBBl5bmAH1em6raqyxeT\nZlVidjkaRlVzy/eXHLJhqTqfX4Xopti7gpMNvVWVqu2TrewR0QU02UDYpJBw/UGOkT6jGzU+\ndv1UufoN1lWIwwEhbqwG2gyAcmzAY/HvN5qdFNrJnc7nx1VFUJ3F1TipctVjmdU6qHZbIKcd\nH4y4+B+E6GSLGEoA0494jf4sCz+3zVSVqlGRPdvjAznRQoNgImTdEaQhPU83yiGXLwlhff0M\nbfTUJk8Qy4BOF8NAAtzTnRxmTspAfTlESbkzsJ0TUxL9xgxlchCgNNi0xFMU7DceVz9rniCH\n2hMTz3D7em1+QYzBZdYqg1BRHaPqCMtwHRoIJkLWHQGSDduao2xVXGp+DZMN0sBeUFbGc6Am\nCkg2/Apce5lpSA6RVgw72WDgPn7FD5c79SZfM3Q2z7EZNVWjM16MLJ6tXg7kG/ue8zGSQTaM\nUj/rG7G1CsjxPEGyYVNxcETJqQgHRauZa3D+wZ2liUCJgiYbTLhHyLojQLLhY6Dh0WGR7DDZ\nwDl4WNgT9gRfBSQbpBV8xGkTKcrBIT0AI4Zs4Dn9WSq7WE+eluWk3uI1QDacT4gjVG7iMFYr\nKuNo9/5jMsiG4TC6mqzQPSovQbKB9CmKyb8n2IQyylvDLvHJcUC7mAujyQYLrhGy7giQbHhb\nDlo6hgPkwmTDYxS59SrfRrtscQHJhq+BmXPIiGhK6CWXQrFkA6lKShPfeEpZdCdeHmeaJ/91\nJq4XTXBMZHFyJnqQHknH4R8heLLhr28vBUplEFv4FV+2RxIkG6bRTnmkOROO7y9JHlX8ymGV\nmNgRnyYbTHhEyLoiwDHSy0CX05zGsA+S3+UUfiJeD+xoNB7/ljmDsU1sUjj+WFC8Cd+rzuhC\nvLzhOJ5VvOLmVjgrqwQaRxaXQyo8SqV5sio0f/9uY0LYUwk1UGd1BeBD8SlfNjcPKBfsrUE7\n7aBpZyssmWLq68i1GetVXo6xQZ/1QY5URsgmCNmD69svSrQhf/ig3TQq2SO+Z546uHyl69sA\nC8RJss5ZdzkkK/fAJvX674m2/OK+QK1ds0Eay8kvxkhL3AKOoOgp/1wnxEPoGszpe2EFnVZL\nUQ14V7UeXsosTmAXE2xc+a9FLmRfSGHlD1Dg1WKV/tileS2ySGWEbIJkw0PA5YPRwPzKZMPP\nwMdiHIfUHBfNrhWMbCDJ3V/WkPTJD/eRUqozHMgGE5eiNvuAh5Nc9cbRE2M8V0cpKqO//CPb\n+8Fq/jYCgZMNLBx2LFHUUymKQuLSxMgGlcBwNEjZchaveZFWDM+nsdOPygM+OqWBJhv2q1oL\nAZINNyPjs5EoZX5lsmEkUcqydyRHKm80BSKazIKRDZTobclKmmX8/RF6dTvDgWwwMQplONR6\njLVmEBo/ERMRf41q7ufFVwAAIABJREFUR6+gonvFOTFRVUkgG3gS6SQxgrI4DZXNUVkMToxs\n4OzThuyYesXcAyZLfuB2lfWjY18wmmyQ+OEOISaf7Z13zhEBkg0Xo764PyxkwWRDZRoWsaex\nED/C0u5hFIxskO0flu8kc/rnaVsmyyg4kA0mRiONfVbDxjoMVR6wR1QxyIJeNnJvr6MeXoxl\nBk42kCcIThOyY9ZgzsXAn4djQGJkg6mFCXXuEiNocQJ7QtVn2duOsTVoskGIL4oPkG3EgEyP\nfFkuCHCMdC6OoHYiItt8CSLUbkYJWqa7mB7YWJ0kd1eJ94AK+96IpNXjxO3Gkxa+cTcCxyO6\nyblUUSS7Hh9FHkSdAvPF9gD3OPvxDNaQC4A1R0a8f+LAHJshqYmBIWqR3IorL6EQrlOScN4H\nNeIzpA7K+3l0l4TrD9CQ5BCD+uIrbavyQF6sNyi5BnYR/S2oo93MLUTOHfcuIfGGzxOvYKx6\n0Gxxu7I5rSVtPbLYhWb36G0apx+d1AyeBliaZTBH7nduiYztR6N3YhWMtxmSGpX2U40TsxDc\nDscTwFWkEJ8hlWNtb7EoWvHKHwGSDT1wgnjDmDoXimzYAaK8rkN5WhGiJJPfh8sXjGy4Tlb2\n3xqmV7Y1rOt2ph5kw33qQSsdbiNlk1kO0X030gbne/AepZOu7+D5FjjZ8ASd1zAhlJ7NUeI4\n9EyMbLjAZkjn8xoSdsYUVlJi3OzQU9RkgxBVlSFlVfIs6oTgyIZQdXSmp+1H4zuRDaSF89De\nI40B/E8DI7IeF4xsoLn/7JWqH5nvai0eZMND6pGqGBaG3KHWLIgoRgT7x7Qwg94CZRwIwsDJ\nBjbxEaZH/7GiA05xJhtmXhfuR9vJhjOQZhmScqmjjIl4h0S+GG2cLFuTDUKc/DAvj++QcP3B\nkQ27KfX358Ac4zuRDdSVuPcXS6TrG2BmeIeCkQ2Xy15Z3k6/97QH2fCYeqZqhZ8eQ3frE1re\nYr4nGqByD35J0gQwzWrGzP0GTjbwPM/NQnCaaNnMd8VJMWQDvzrq4SZrhf1+dEYVy5C68Zqj\naPFTIx+ASxykJhuEmFXq2X1i78QSnyRcf3BjpP9IRfvXcAYvAgX89JtnyX5/v1+sgA0Lez9k\n3oiLYZNH3h8Q4Sff3DYn6JB6X1Pw9dJSFa9TR8wwQ2NnAbPkyyLAOWU3UK+VWPkmfDodZQNT\nIbpvsKRS84Uk5+I4U7uiBo6yDImHzfN4Ubbv/1MrE5+4L/SIk/7+sE56rfRq0xOvPzhDWkP9\n8U3k+BnG7/KmNfrU8hb4xX3CJz6cGx6iXIDSb3qW9QOL2fX91v5+UyLfFONLnoHc3ZLmplp7\nch+dvhlwD/ALDOzTfp+RDAddxXnkKxSJCcRGyPO91Gn/UcDZtdJKwLBDYSaipob1SV56Otk/\n4eBDvBOy+3579+f9ERcJjmz4gx7BPfwEMIhsWCRvWs2+VmqkrAitjcTIhtwdueKzGoAZ5XAe\nhXiu8fPl8CAbJtMT9aVYbrOksvyUkaQqWRknDnqARPYZsjk9m6QUBkRXFDjZwFzBI0KczafT\nkxrft6LIBjnA6ytCbE0GbGTDRXL9xsVHK0OiFIrrz+BF6ii/wUsvOZ2EJhsKguDIhl/ZtzvD\ncismsuEnedPKNwI6qVV/R3SMfMmGl3v+aC3vapye+daJsrqJxoqzKNRm5XrnPS14kA3z6XWd\nL7JsWSjq8lP2qFCBdexgO8Y65Z+B5jQP0ze6osDJhnOgepCbmWs7j3iVV6PIhnFAL3prha3a\nRjb0YcHMTsqQyImYo00Ur89RzHbKJwxNNsSBH6dtlp8ORhMc2bCQOyDlcJ3xncgGipzLLG/F\n3e2I6J37kg2VMcpapmDWIc0RDgrqRSGgBSEbSELoMzn6tT09/OByC0QzMaw+MQoljXaZXEmJ\nmO4VXVHgZMOZ8ij96eJw1uhL6WReiCIbbiUWYZvdU8R2P45ld3EjpycFyg7lJXbe4uh658Aq\nTTb444H6g+r/IESJ2C3BjZG+Y1qoZoR68LfqZpYyH7WE1OFy02zjEXK3vKA2rI6WfOhPdN4t\nXoTqoVpUz5CbAtwjuCFS/tH/C+cuky96cvdMvk8ApZ7hqEj2WB1Jr6PoQc31wJF7NoRl6uzI\nKc/B8X/dxHZ4tDATTrNcfg5FWLhmqCnCCMaQaq0TvzbZnlxDUtx2U1tvY832WcqQrCAyD1Gr\nWMgmY6j1hfr255Wz1XUiuhfwhFd/Fv3+vITP9i65REkhmSM+J6y2M4Kj0Z281AJGR+AIJv5J\nzbLG99TyRCv4Ex8xdBVwusPuo82rRFoZHGuuFO2UWzvlgvrFYa+ijmAMqYlsDu++PFFDSoxs\n+Ar4mroVZtcne1pm/Q+UIT1slqlOE/Ym/MgG2Zfqb325mobdXNmdk/n5Zwe0gpANBuxkw2jL\n7MnJk7MlnYwOZsi8GmnguOgagiYb5qahmzpr8tkeKzsz6RgRRTYQe9DlF9heJmGygdrVZ2nh\nCzpdig/rxSdel7dSM+V84TXZ4I97j3pa5PYYkBG7JTiy4TPO69vFemNvvhNQU4phRYV69pzH\nfmSDHN2fJf+s+/KZfeqlak6O8BNen6oqCNlgwE42bKxI1dMkJ723M4jqOAHdTJ+n29TRY3K/\nFJxsmPau/QF83uqxEeVBg8r2OD6KbKBknSd+abE4gsmGbQt5SRrZ9WyInGSjhRzEKWlIFfpL\nk1TOGWs12eCP0K8fyO7xq1fGbgmObGAXGnEWyhpXIsdwZrN3JZqY8agEP7LhGn6g/izFjpfE\nAxgJYHGe3JhXnHRbC0I2GLCTDaIhqpdhf06OfSOm/RicaVqa4eUak7e9wGTDlyhmf0InmA5y\nHI5HZPxg+cd+ufO3U0hRu6fIEc+EvB/HKILxFNONiVUvmwnxgjrxVrxylLyOzi8XTTbEi5Dt\nHPMW/8r4auqGfJG3PoCP9+UYKZ/u+U/GulstQ5prljsCZ8ZfaSOaQ8mjh+mW9Rs6I4w+cuta\n4IGATtz20Ry9KuFquVSfjvOIXNcS/cyt96ujNw32kHnrH68FfGVb9wgwUC29Qychl+TY7Ur7\nHt0zKbFEC9lK17ZXVQKX0dLxwPu8bh35eTfckH+HtJ2TgGO5nHw91Qn4qhWKjyANKctWdt+c\n2YwZU1flipxVAXzIu/5pLo1lZhrrRlhP/jdmuaNxSvyV1iD/lhzizy5Z8Wd7myH1lFuzgCcC\nOnHbx/XpD9bEpatW7ePGb4xc1wT9za1G5pyGwR4y5zfKVP2+bd298gerpc3y9fGYXBoOnGbb\n469M61KUtVUVSkN/Wmotb4Ra173EYai7KvdmYNibwJm87gbgsICvWqH4CNKQch0UjYMjG97k\nCIrnrImW7Cus222NAE5Ek3AXxY9sKE8KIKFKcv9ites3sRkS+WEu5KjYgMkG2R8VbUlXWWUe\noz5eAwwyyYZtg3lto+gaCkg2vEmV2rUnx1LmJoWZKk0O+VmsDBfYHL4U4SjE33fvNuZnW/Fg\nlbH3UvLO6gbc84GpCPkUXVVHaLIhDuQueH/afKfeZ3Bkw6ucEYt0N1Rfe/PFfKvJ5cuiBHra\nE5H5kQ3FiLHdg1gQnfEVy3oETDYQzidLkR3HrmVxlfxaC5eYZIMhzhOlMlRgsoHD+OwqSLeG\nHX9nAx/JPzkNgZ/DBf4IX4owfbR4hxwS1aJp98NQznoDXk7+wrLr+MjvxUop63pNTS05QJMN\n/pjZuEXfvi0bzordEhzZ8BKFfvPDtpa/5/CsTAYRd5vNMoO4jAEfskF23lBepa5jlON+FX2Q\n18u7NBYLnGwQnMouh5j3V+rwLFZlXGVZGmf/CivFmSgg2cAy3/b0bBeH878v4uRIRHmovwrz\nbS8V6y5szSfxLYqcss+JX0vTsMXJsWr5CnW533WVz9dkgz+aceDfytaxW4KbkJ0E/KMeNiNV\nI8+njySlDevyjjGm7OMBaYwWs3VjyD8Ir9EHEdDPmPYaNJ4jW18MvNUYpKRe2uamtJPPo3qg\nh8sbSH3XiGjBDjaG/RXlo9s+HOYl8YnNkGwmSm4k1H0rq+YHGCSXsQt2p/tP7Zz5IYRgDKkR\nv2x2xjC3QRrSk5zEiqJMDV0GzpQyt53dqeYt0j2IDxtIth771oc7dPTBwqMtBEeR+qWo2z/w\nKf4oh/9HkAZrvj13bD5Q5Yxoua4CYpH6cXaVuaN4+iwCvcghOHTf6HF8t6bYDMk2oiDK/klZ\nY5qVKFaIu2SbJbt89cLtwNeHoPAJIRhDmtRo4Nhxgxo75GwIjmx4iO8qKXYoXYZsDm/+qZtd\nFZJ1D0x4kw3v8nMyc431yNxNXmILaKnBhG5L7uJeTeBkgxAfUay5fOd/dgypgsue5b3hNrQk\njrgOGU9E1VAgssEQ/LFH2jVETFKRz4C0N76hgj8Ibvvl8FHtaF2A33f3APsHTrR5klAUyM4N\nyk9o+5+8ZiHcpFQ02RAH1kwac8dEp6FicGSDkW25NHsKSWzmvKxLn7ELfn8MzLe+eJMNKnDm\n7b8sQ5p7mPxYTe1Stao4oilnW0gC2fAlMDtfDsW+6YIOu3auAx61yAZRBcfeAKhMBeMv2R46\nrQH1YgtENhjdtJtsq6oiZuKc8sJf8TYVJEqU1SaUp3qYu1m8gy7NWNZCCl9w2U3YsFaJYG5R\n6QiXuob1abKhIAiObLiT9VRJZkPpMuSwIa1cXyItTDjNtIfCeJMN7HGJ4ctMO6q+tyUoA/kQ\noCwnYKYReRLIhnnAJ3TQRYNRuXplaflvhC2tAU4arQ4sZJdz2DLlIV4gsuFt9evsWb8c8j5T\n8MMQpvfqyG930ILhZ2GJC2zNJ2+H24n0Sw+/oeTraPFKUmy1LndOj6Nc3j6abCgIghsj3cJt\nBHkKfaxWcKT0erHEpsoTqX7iCZWYrKcc9rfl3AonsdLuNsqjmc7aCokrJsUFecAp38nq13KK\nossiRIVaovs42ckiVzVqKc+E3Qd3//C0soe24TURwzIDFFA4gJNI0DUeSAsqxaBdioUGlVex\nXmx43VfAV8sCTQJSWFF4DGmUelX/aMkqHBE1GBYcnvdOzI7OkF39Culo+zMw/XjuynCM0F5D\nfRcIxwkFi11puJuCFHZfTwepGsGO9MQQygRDPS9qtA6HLbPkfoJcyquVRcPwmp3A/dGlVslS\nffmEkCtyytDf19RVsHXTZH+UfO962eeJKBvbYvccA4cQUmlIiZENV6k34W+mrWQ3UPfdjnX2\nO+9NNjwhRyfd0EB2Br/sShWdS0FCNP9opFflidEkkA0UM3UCUJylXAm/hsmGfyZsDg1XPumk\nv1xK9rdEAcmGk2U9w4bbm9eNylE1AqQVcbpyN3xZqN7uR7JlrsbJBBV+310L7OF9op2Vo/j/\nn5XjhEE2uEOTDQVBcGTDpdx/DwucbKap2OKRZfap+FMFb7LhYdmaDUWZF4E/ewPtz/9FiNml\nSC/hWeMBJzGuJJAN8sU+uCHNFo0xjrNkacTmGUrh6he1kfi1gpANIWmMeOIm+3VaoYY0ESCF\n1K484YTexH6XAFYUly+uYhhtFlm8g7TsalGSThsrR906QwTNIBvcocmGgiA4smEgmtKfP81J\nEQ5qjp50sceae5MNlJ1sPHAMsPEClksUhiqi0afBxSIpZAMFTlSgnuS9xnHWRFraQjUhbCR8\nIOe2gpANNH9ddfM4u05ye4esz1ug0u1RQ/xTumx4UCx0inxxVWY3JsbWfNJAqkgxyueHd1wN\nvDBLjpNEHBIZmmwoCIIbI52tgmPCSkH0Bh0SVagiromzurFAnuKGd14RkaDsPeMBX+C+b4Fw\nMkqlY/B2U9IYUb3HP1VbqCQXjbyZ+4+VQLNXxKOmf6JgwVrMji5miCmT/n1Fmo7tgWPFmbIf\nV59fJwZIla8ERTPZLrpsyirekLxrVYhQeAzJSB/7r1LMWjTo2aixMKOOs6ShA26SD4Warcy7\nExVtr0Ll8YbM/UhPGBdYTe4BdkJiRPXZs2W3L3TLCJUkGWcX8GBL2EH15TC/sJnk6GIyx5iu\nu6e3QPqp8rf/Pmy+uEga05E2cTA5FComW7YWCLdSPKGMauHEBocwCgnZkP2H6KjSq25Wak/9\n1Z2P7u23tOneeJEN/7WviNpqtrKE2HLrV/ZtnJYk/SFaTAbZwKmEnpEj647qJ2yJ8g7shdI/\nAUbUIqVEV2TDPo+H1Z1s+IGjQYgK/EutYJWLzdHFQir7HoapqGMmLFdc+Z3oBCuRD+UtbACs\nqxShHRhSoUvEAWiywRvJJhv2LnS+vBFkQ6hZ2odHoh8t7gPGCaXNhp7dok3xDJtDphfZQH4N\nbcjLIHaYRXFKla55mxeTQTaw8jY5f36oelPZURZyF9JmypNTT3ZPYZINfTwEtd3Jhm9Y0PXb\ncE+VRoAlYsd1ffhotefwpGyYLD/bCnwPvX6LbLCA59Ii0xdWs1pVTTZ4I9lkQ/+wmBbByg8R\nQTbI/s64OoZ4Vkm0yT7mKBJFRezYdABK1Dfmaz1HvzRAGSQ20mPQPHrbJab8QHLIBmbrSEV9\nNj+D1fOiLO0xIOw12l1+r04twO50lpJwhjvZ8BmLzJEgrZFskdLaNogtdyEf7UX1asHh5upr\nUcq4DQ8gHZC9O/kZkXWtMXeD6SJossEbyR4jtYwQIRzv/N79W/Z1yhhZ4KpRPm1OC1c8tuDF\ngMcDFwZN4vxPzeHHZCH8yEESK0BwAnDS/f6RH9qYcNKXgEd4C4ncnUwCZGfItf84a8z54UMO\nNKJcA8YsNglDxHgICWNS61UjFMl8j9AcgWEePLLbq9Jp2CIuBCU2p3TshzxSbkhN7Q9IXqPY\n55qwGBihlBX5HWio5ZaPLUjh56X9uuISJCB1tdLajdHanpnciJpVdOrkwL6af0S76O1yFMMB\nIsXIG7sjvWlobLh0/5Qj32WJJYqGVEmTWXbu59hyn1BLg6nsvWpzKJpgqaa2ozOiWFhE6j8e\nSSsuFxopJxsa2kQIt9anvFfGjvbuinymLlDq85zTqiTCY+JIsH+P4W7nQTZwON8osZqKXxK9\nUY4oehiLySAbKMsgePg2hrR6Ou6KIhv+k0M0KtJvuxzbF/9SvmnIJWe+awS38CIblNAFTRMZ\nE9X0DnK4LqGZTUEeqirK3MonN5lSlTOoeSzD6n+lrra/qDgnBauYa7LBG8kmG2rb2iAaNZhR\nthFkw9vAaSZbdKI1gLA5kJkgKWBTw92DbCCXGNwi/vz9cJsTjImfYEW+JYNsCJWHKaFIic+7\nb48iG0IqtStuFjnnkLt1fQ40lI/0EcIN7mSDEroQ56abUa1nSIN0GCWEFnWTfeIcldCaOpQK\nU62LSbPflTj7UWRflLUhWXdVkw3eSDbZUC38/mMPy0pV2/NLPoJsmCRbKtPHuIdlSC1iq+SR\nvOHW4jH65RfvXWLHvkvQPIZPWA4MNBaTQTZwZK8aVd8tl86MJhvM9JFPkKM1bhQ1SYNRVAea\nCLfWz51seAGgh3N3NTP33ikuigpbBnMESjaPgqyEGB9aE1DUCajJ8wWR40eOrmSfLU02eCPZ\nY6QKdGe+rcKz5ZepR0jex5V3RHR4nmBX6Gm8/JSVCNghoy0njHNKoRAJHgpQxrK1N8cOGNbz\n8Cl5kAOzDGV+D8KJGjHmdKYwBXCttKtGSs64wYWJpx59xgjNa2imDDvJSPoag6tVcPE46hSY\nvCe13ON4YS+dUXOWEesasRt7un6Z6GkVQaTckEpT35+8Kje06DTQsJBdsjPew17oAaC8lR+2\nnmlIDvQcx7HFjN9jwA44z7ls3MWBoMnDlRZNQumQLorZfrj6dT9wFqUrskrLsSCP6WqVt/sU\nxIcbDRekI1BFNRiKA3TALartoiPZ3tlmXreNxovr6OhA8lMowfn+dYaKFlJONmTSnN8Aefdu\ntGYhsUG+6A6zd1fGwfbia2EakkPU20xaX1WNJz3IBp53/Dki9aUNA+qavFQyyAaaka2jlshL\naHg02SA48pe9/55RImFllQtryUy7srkdrmRDfgk1Wbr+aE56trtTu/q23GE2hLLuQxp1rEKl\nYM8pUooU0IWK/KOW/h6afrOjJ5o9qYL/NNngjSSTDWt5+q+uvN8d2WuL8adojyrv1Qm3CypR\nw3fqSzvTkEbHVqmcplXT5UE2sMz2P+JPLx8lQjLIBrLiZmrpJXkWN0WTDUZq11+FlUctQ70f\nALfWxJVsMNuXtbcDr67O51mii5wKhhZldVV+880jQoMryr6lxCwO2SI3xnJRr68+FjukyQZv\nJJds2F2VE1RVAbpYQx+aqDgWxbqhvlXyBqOhYnQ3i0VnxxLGmxND2UAcR7+51Ah9SOl/WofE\njn0OJexICtnwh8VkkwfDuBiy4SP+Dewb11L90JyPjF98kvMx3MiGXLl/aVrY/Q/QCJexJ6xz\n1nQr9WX/CM3kumpsdaL14uqZ9kbEfpPSzLgVTTZ4I7ljpCXy/qTtDZVBBL4mfekGtlcjpQFT\nj4Swkpc26O/QnuRW5W3tf3O7Gp0zZxhab4NdSiQd2RZN8q788TNiC7xKp8c66sY7Y5vpM9Qq\ntrAXOOk7LzFZUOt9+rzZe5/fetoFGDqquWmWx2BX+9zoYEy/FvlQQYoNiUWx/g5nOlKYTgPu\n4jYXoItpbV3ji0r9W+4jxwpbG1W0dz7ecgrxYRXICIWqA4uypqjPX87eNdvS6O1CS9epH/OP\nSfnXdyjtAXL1Nia42aV9GH3c471PJHopLwc1LP01saMfWkgt2ZDHcyYvD4gypEf+Uqn4rJ4X\nDxtM3lWJdNyU/ZdTnaegFAWgIX2fI9lwDfmBkjZk6S5yBOVCNoSRFLJBDvKMPLg7yQU9hmwg\nTrmUovCV0x2WZQI1yImngvMx3MgGygDGYtLr/6XwVvBbxpGsDGU5d2L7KfdvztWR4c0VaLLB\nG0klG+aq1uN0OMNME7ONGW+TSlNiB2M3O6p8X4TKdXn7Kkey4WTZJdxCoQTs4JcaskHMv9wY\nl4fScbaIIRvkWMF8BUxS14Eu0xXE32U6H8ONbHgAKMZjuLVrqlkX9UOnkqFFzsOTC9CE/jQA\nytaIjkaOgiYbvJFUskEp9hzWwbrL6RGGZD5iHP1dztTifpi3PZzj+Gp5I71ff2Nfp9HvCXLL\nvfR4ckhGasgGGyrjRhFDNthgamLJDukWNgXn960b2XCnORrbvbuBdVHnOhbd4txaXKo61LVk\n0+nXnGiywRtJHSNxpx0VjrTucr8IQ/pG/PE0mQulLg5H7P3MCVgmuVT5X55Kaeqsb0edm0sf\nRTjVVmrx+gV/e26nTmhT1iWZLLihfTah6m8KM5snxbyd4sJwVJVnUSY9vuCUQxmpNaRGfGsz\n6lp3+bYIQ7pZHMvBM5x+PjyHwsEzb7tW+jrvW87xzUNOzBeOA45xHGAddKD5o8HcTr+rQugS\nsv93mqCC2WBaw9BivppEdtyFtA2chqKMY49Qw0JKyYYNRrLSEhynR3gswpAGipo8Ed+FvoQj\n/u5HpQeu2eNMNkhMUztvdCIbaLB1/k3IUB52KSIbIuFANljY3ScNo/nazFTMWW3HnqQT2fDH\nI5trmYL8Yv2/w81r6pyX0o1seIeS6FBf+cbf/bLcaLLBG8kkG5ZaJnOqETswz/L/UY1QRaSv\nMnwZJlj7Zd9Owc7OZIOw/AFWOJENFOlzfBtTvTpFZEMkHMgGG/pXmFuRfs1C0UYO+CMSf4Xh\nRDa0x7CyStlLENlwh3lN28YWFe5kw+cU2ddX7nb3Yr8XgiYbvJHEHLK7siyTefhy9XdxT7sh\ntSPv/Q+NaYwvovZ2JhsIL40gz4UfHUa/eQaZYUxsppxs4HPyszQmrX8XxyOzZox4l4IT2VAL\nZxezptN2737YvKYuwb8uZMP3JOdFV/OLGMHOaGiywRtJzCHLfg0Kk64G0qTVbKS3HzLLq7UZ\nu9Jkv+8dURs49+t4zsNCQ6X+GQ0z0WX/hCpLMXhIuEb0QNlGMUpaV9f51mWv4jgV4cAq8UK4\nlU8EW9NxO/tXZCV61ocaUppD9gfZiVe39/WRQKkGyMyXA9s0lDXSxYFVogaLUmi6JJ7TCONR\ne1rTMMz8fD5TIgcXWJJ1i7gE1TrbErgz8ovjOueddgLHAQ2s7tYHpiG5OJC7oQxGUcxRizh0\nMA5tpDKH7D8fAlOuH0+3d4l87VZpL8fG1wId0LYBUNFqrfrvdYgHl220F/G2CnjRgWww8/MZ\nHswHPdnA4ExO+8SHJf73rJJiDONfJTlhkg2/HGVJm21gFaJHjW/r/11nXs2YbH0MN7JBVMVw\nOdyqOUtossEbqcwh+2AZGspSJgTkyK7H0QNwPLktrP5m8+FyGGMxef22hp8IG1zJBsJ/wBNb\nP+sW7R++jNVCYb7GCwHZIBQHXlL+DZH0cOTbY7FSB2eyYe/Ai65DpmkPf7LA8ETj29o1pC2M\n2l+ZEa/RcCMbRD1pqRwMqMkGb6Qyhywl+PqB5aMzKJCo//KrvhfzypLzTnuU/+DUuwxD6r0m\n/ETY4E42CI5yvT93FDJMz9Y3VfS0fPDaU5XGi7twkA2rYNLYU4DIp3WuEjxisuEzoGV4+298\n6QwNLrF7dx5w/J2rdlVO+0Y4woVsEM1wnjic8k9ossEbQdLfIds5hv75mzF/6rLVf69e5vTx\nPVEKH66m7laZvz+V71besIo+Pr7snWWrzWi2TtLg7nOtxfljVRquXt0FSJ/NX99F+le0YbpK\nMnzY5wlUlfIPmiRoyksTgY8itk4G2phfxzM9/onx9U2+dE+FC5fB5XLp+08TPHgLlFxcHQNS\nfQ0O/o9fpwVnSFm2sns+mM54Z+o79On0QRo6eGL6dNkFqTD9SflujSrykmFITWQfb4RrLS4f\nxXDGy7TzWP56A3A3bRjP+njFXkqoqlR/vCt/fwteGg08FLFV/q5SU42vSnV4vLFVifDfHi58\nSaun9ufgcqDoLuF8AAAgAElEQVT1XCn0TvU1OPg/pvml/0zAkHI3xa7z6tpR/PJKDo9tQCOl\nEZE77smzebA6tJueZIOohOM5fk/p7rxkhJ9/C3yaZk73FxayYU8Zk7T+GJgXselVRUwT2bBP\nzcCZgj5T+ZuZt2j9vz7HcCUbZKu+OB13CE02+CCVE7KUs24dz/m0EKHSdLdsWLRTlA0bkoMO\nlSfZIB+A6hyfrTInDGJ1KyFmAbM74jSzUOEgG3ZWMknr2dGzY0TozVJkw9vqQhmDwj85traB\neXJr/R5AV7LhNM4m+4AmG/yQygnZXfVYLOpI4Fj5TJwTeRXl4JYCBzIOoyeiSkxGHx+ygRyf\nWdhYNbg9OSORIIHD73LnWS+twkE25NcxWcvvLUkyA0+D+W8iG55UhmR0MAbzFytH5W6/5sSV\nbDgLGMfuWZps8EZKJ2RbATu4h+fst0JMdRkOjv3ccbsX7jaasgr8fukMXN/x0hBFthfC5HJN\nzR7bb9HRIRRBaygSjVW/94nNfCvOYJfx6wt+7AHAiWbWXg0PpHJCVtyD0nnc73L2W2lObdGH\nxRChaxMnLDdylvJoC9Skbt7T0a4BhQJHAT/ywnJgZEQbOQqmuom4Sv3cm+qnkVNiN+DoSnCY\n10sUr/Jsnh8jpZHSCdl/Vt/zqWCtrYGxG7P2iGNBiieNXMLZvMmG501DIomCtZXJ8QhjxG3I\nsLfshYRsaE1Kf4TsDMqhEcYr1GaXVmSDEdOVDlaik63ImQuftcZv+082cAopGqJqssEbqZyQ\nXa2knZ5x9FtZtJO6FWXvovfxq057e5MNZm5y0qI39CVxnXy+6tkLFRKyoYuVlFy+VLqHPb2/\nUD9rDZMNYWaGiIljEKGouv9kg3LS+1qTDX5IeTYK9mYZE7tRDm7fYjPobo2gI+FNNvxA97+i\nfD/fv+/6ey9RT9gluYjMxVBIyIYhpsQx+4K0t454rfpZV+ykCxmeK6BUuy0ipYX3n2wQu0ik\ncqEmG/yQchF9eYvg0pnf2bn9GpbCeS/x47Kfd6dWwJ0fAkailJOPVk9ZYcMf/c0LMJJ+xiLj\ny8+m5ZDn4B7LjjgpS30lMBwEyLFicUB1FWEcBIYkHrzQ6131suMskh843emrZwM3vG49YbTq\n8cSrOojA4v9vGl+m0xeKfCUNvM1hQzpFULIcFzfvxLGvOmmbafgg5dkoXHc0xwLrq1Rw7OF7\nkw3cC/pkSTn8ryvsmGwvU0jIhnDIPCX6otlRBovekTWd/M8GsTL8E2ssI8G8iPntApANJBVI\nQzRNNngj1dkoXBFOfbndeRDhTTaI1YchPU8cjv5VIwwp4nQKCdkQ7lhtIJH0McYXTvM5OxM4\n9u9/xHn865QM5Oj8K4HT7S+JApANRKyn5WqywQ8HAdngDN/BrTfZQDmV6pMgZOUIO0r7wV6k\nkJANtls/BJYk12wKJccC2Ykrf902mnO7uwKeuoDWDaceYETgSQHIBkp3Rs6JmmzwxsEwRkoO\n9jwrR+UXGgZUyvh7barOJiCQ1JhK/WXw+4tZX3+iqI9q//31fv6z9C2TMiQH54yw69GFgdVV\ndFF0DYlxk8lkGX8dfPYKFVbBDO8dr37QX9wG3SKqqfD5yVbb63dfNYLFwU82uMGHbFCpLx83\nGiTZJapOapSRXYNCRzaIUKaZKZq0hYoDmziB9aXrS2IkrZ1iyad/b6+iQGSDgiYbvFEIyAYX\n+JANKvUlZV0uDfS5ETjlaiubuIlCRzZwDr8reIFk0x/vPkLpbJ0z2gifX1a2vpLYjHRPLBDZ\noKDJBm8UXbKBR78U3Hc8MGJtGno/CVSOLFH4yAbxV2W0ESuOHcZi3uzKSvNkPS4CxqvD7Wa6\nv/Z3EVUUiGxQ0GSDN4r4GIlyyg4d1GSpaIILv01D45SeTCBoiOqUS3pHT3PEt0AutD4jTNMx\nEe6SbFYjaSjihvS3OQf77hk/iVfKHBzJXAqEpigWuh5Yf6IZQEG6z406GSHAEjeSIZ2cuhM8\nRFHEyYYNQBl3pq7wkQ3sjrp9sBweNQQu5hXbSwLV27FjKWPr+dKQTo2sQpMNFjTZEI24yIZ9\nZWxZLGJQCMkGyhX1qUrHVs4IO5emVe5IW2zkK1COqzZossGCJhuiERfZIOa/5NFkFEKygTIW\nnV2dDWmssUZ28jIPs0VNUJq/PpFVaLLBgiYbNBi/psHIJWWGOz6cTk52l1kl5iMyqk/jQEAb\nUmFDc9N3Yb655kHS+b7aKrCtLDAgJad2KKOIkw3eKIxkA0WRK1h5nFmJa2S4xIojo/WDNNlg\nQZMN0YiLbPBGYSQbRAfTkKwxCYf73Wwr8ueEqPGKJhssaLIhGvGRDZ4ojGQDSTYywu5OJFwc\npVMbBU02WNBkg4bCH2WUIXW31rxFX53zHmkcKGhDKnRoyHY0Ifzq/ZC+35/CM9LQZIM3Dkay\ngXUzKdWhhQ00r+SQ0zCM/7N3HvBdE/0f/7aMgsyyN1gRBVlanCCiFEScKDhBAbWiKI8KiqKI\n4ioiLkTt3z0elSr6uBAt7gFCEaFAGUKhQNkto1DaQu9/37uMS3LJ5Tc6gHxer/6a3F3W5d7J\n3SeXS2A2GArMBruOVbMBvw4aF1NbbDhhT4eXvVYRmA2GArPBrmPVbMCaXOeFlsv/aDC/cilV\nYDYYCsyGQJoWss/giMIHSUsrZmcCaQpAOuK0xvEZnI0doJrynhOoTBUlkBbNwpcVJNAEZkPU\nzYY9Ve3OwubVd3gPGhSYDYYqt9nwTJuhbTIIiXPGBGZD1M0G8vkUW9suR1UAA7PBUOU2G5rn\nkiXt94YKUmA2oEI2G5zyzEhUYDYYqtxmQ3u68SeSQwUpUKCjRtEB6amuM0jJhddVccYEIAU6\nJhQdkEqXfEnrWu9LviQSmA1RNxucwk9feiowGwxVbrOBq1RS/QzMhuibDQ4FZoOhI9xs4MqS\npA3MhsBs0BSYDX5VskOYOVDAtGQmXrKLg5/g5+j+iRJIJQu+mDVfZL0wbaamzCJSmBn8BD9H\n9090QJqb0PHKK09p95NIEr8jrU9zx3jzdg/IVxQqLgF71iquEnv/VV1IsvMU29i4TbGNkhWH\nFNtYvU+xjf2rFNsoXKk6jo3bFNvYulmxjdKsg4ptZB1QbGPvv8q8OqzYxpbNim3s3KC6M6wp\nUGxjzV7FNvLWqbYh/YkOSB2y8De7mzNm68yfXTXnO/e4n7/+wSMSlT5bkWCuKsHP334faYIf\nv/5JkeKbuYoEP3wTaQLvjER9p0qgzu5vIj4f6rz6bo4iwfffKhKos3u2KkG6chtSfRcVkI5n\n7ciCzs6YkpVZrlqa6R6X9fcKj0jUsn8UCZarEmQtWaZK4LWHqBXK3Vy8XJFg+WLlNhQJvDOS\nJViqWoXyOJQJlNmtPo5M1W5mLlGtQpnd/6gSLFNuQy6Va+4LpNTjr5/8+NCE1/ykDRToWJQ/\ns2Fj6qRHXlU9BQgU6NhVhO8jBQoUCOUbpER1kkCBjlkFIAUKFAX5BmlGWe5FoEBHuII2UqBA\nUVAAUqBAUVAAUqBAUVAAUqBAUVAAUqBAUVAAUqBAUVAAUqBAUVAAUqBAUVCEIO3+3+eBAh0D\nmlu2IG1NywkU6OjXkjL+GsXWtMiWDxToiFBZf9bFC6R8rwG1clXDJhXuUCQ4qBq1juxSDf+U\npxr+6XCuajiubaohv4pVY+eVqEZ3JLtVI5PtUY5MlqsaxmqL6nwos1udV/tUA48VKEf0Umb3\ndtUIawdUg4LKVZEgBQNEovaoBojcFwwQqUs9QOQK1SVjpQrW7RU/QKRMXiDt8Lq+ZCsHb1SV\nngPK8W23qK7k21QUHMpWjZu4UTU2Y6Gq9BQpx9D1zEjULuVVNlt1QVivOh/7NykSqPMqX3Vh\n260am5nkqMbK3KS6YuxVVgCkqkiQAgU6anSkgjR1yLiyWXGgQOHoSDUbBkHXwGzQFZgNhqJu\nNtSHu1XbZDpSzYZB0DkwG3QdA2bDwpSUgxViNhwJIEViNgyCLoHZoOsYMBueB8ivELOhPtya\nkrJGtdkjt400CCTjIwc6asVBqgDVh+sBvlSnC0AKdCQoACkwGxQJArPBkIfZwEGqELOh8oMk\nMxt2Jif/wSYCs0FXYDYQHaQIzYYHE84Ow2yo/CDJ2sjrAd5iE4HZoCswG0iUzIZboWUYZkPl\nB0kmAySFgjaSh4bF96roXYi2otJGQpBCVQDSMawroWtF70K0FQ2Qfm4JzUJe6EgASWY2GCAF\nZoOu0M0GB0iB2YCaCdD0SDAbnpcFhmo2GCAFZoOu0M0GB0iB2YBiIFVus+F1VIPXX3fGBGZD\nBZgNDpACswHFQKrcZsP1Ne8YO7bO2LHOmPJoIz0LoCIifD2Q/G6ZrbusdEy1keYmJvp8FY+B\nFKrKuWr3cc+FpK0s4ogHqQ2MLLN1l5WOKZA+Acj0t44jASSyaeBjrWTh5WE2uIAUHbPBG6Qj\n1mwoyciwVJOOXLPBCtKRbzYcnn61LLg8zAYXkKJjNlCQDgwZ8pVLgiPWbNgBMF2YrYRmQ25G\nhjDnbjZYQTrCzQZSsuCLWfNl+VQeZoMLSNExGyhIewGedUlQWcyGvolThHkfZoMNpJDNht15\ndvKibTY8CiDcwdzNBitIZWM2PJuSosqf6IA0N6HjlVee0u4nZ0xIbaQNGUsqYxvJA6TKokZw\npzDno41kBylUNYNRkSzuQzKQZCqPNtJwABV/0QGpQxb+Zks6G4QE0u3QNAApLB15IO1LT/f2\nso9JkI5nlbSCzmZI6Ya1TH/PzC8lpfnSn7y9trDboUk2wMtsltY1XBZjP7Rql6PPTgXYI0lS\nuN1rBfizqcBzG6Vk19Z8CtJGCpJLkkO5hxXb2HBQsY2i9bKIjU+n/KPNFm9RHcfmPY3gViGM\ngmRNsjvXvth2gGfEsNwSxTbWW89HExhlS1KY470CW179AfCJPcmWPGF2EsBhc5aCtL6U7Nvk\nXHMawFJzdttB9z14C6BJPq37eWfn/o2W2fowGOAmAFVRiQ5IqcdfP/nxoQmvmSGFs79m+nzm\n6iJStEr6k51rC7sNGq0BeIrNZua7LcZ+LodTlumzUwB2SpLsWOm1AvxZvkWcTW59tj3JuhWr\nW8PwvylILmspyNyv2MYy2a6JP7syZRG/ALymzeYvUx3HipxGMFQIuwK6WJPkLLcvthlgojB7\nMHO36jis56MxjLIl2S49DuFnX+YBYfZrgI8dx5EtzE4EOGjOUpAyisjmZc41fwTwtzm7Ypf7\nHrxAQVq1bIf7Tq6b+2cR2WLdRn24FGAY3g+9z0KUzIaNqZMeeVXWas6a6b6Qw2wQq3YOsyEv\nLU0wp8IzG4rS08VAq9lwCzgM/PIxG06Iv98RmgPwhjZpmA2fp/0jX8WOPEXVLvpmg7NqF6LZ\nsBTgU3uKijYbOsHVcrOh3Kp2XKUS284LJIc820iLAL4w58JrI20BeNU1UgISkbaRNiht89DU\nEO5yhAkgGaoH97it4ghrIyXHJ8pAsqgC2kgMJJsqAqQsSdqjEaSWcKu/zflUqCA9Eu94raaM\nQXoy2Z44MpBugBOlIG1PSTGeRpUJSA08E1QWkEokLzZ4geTo2SCC5OjZYAcpnJ4NNpCsPRsk\nIPGeDR4gRaVngwIko2eDDtJ9UMuaePdeBUjOng12kLx7NvSAS2w9G5wghdKzwQWkfb8DzNJn\nZCBF3LMhzqNnw6+JNRAkWc+G8gPJ9YGsF0iOng0iSI6eDXaQwunZYAPJWkVjIN2YlCIE8Z4N\nHiBZezZszljk2KSPng0KkIyeDa4g5WxWgBRpzwYKkq1ngxOkUHo2uICUO0cBUsQ9G+IKzJ4N\ndgP+KwAESdazodxAcn8gGz2zwQ5SOGaDDaQte8mhpKQPtDkG0gkwTEggNxtaQlz873zS2oB+\nGKo6Nqk0G/bQ8+cJkmE2uIJURmbDvLRvtSkKUlTNBheQ8n9WgBSx2QDDTbPhHwBL4ddAqlCz\nwf2BbDm1kd5N8fWyg7ONVALwuDYpAYm4tJEAfpatXgaSUkUqkAy5glRGbaRr4WRtioJkiyub\nNtISBUgyhdRGguHmrAykwenp7HqQk5KiedAMpKsq7oGsLiVI1yaan5WQglSal8euMp4g9Ycz\n/OynANKPiYlYN6zMIB3Oy7NU6MMAaV1KivxGcYSAdDg19W82V04gXQbAHobSW6NWxWcgQXmB\n5Hwgq0tpNnSFzu/rAVKzoQDgGfwvMxvykpN/cwXJ22yYBbBk134FSILZ8MH45/RQASSr2SAD\nSWk2FLiClMvPaiRmw3cAOEygu9lwu+YIy8wGC0gVYzYUAzzB5qJkNsBw02xwAWk6VoMpSBfx\n0PIFKbwHssxs6Apwjh4gNRvcQEKzYSPA664geZsNCNLa7QqQBLNhCJyCIbnjxy8TQLKaDTKQ\nlGbDDhVIkZgNGkjuZoMGEpoNCQkvWNNYQHI3Gw6lpWFOu5sNs8c/jP/8mQ3J+gwFaUNGhhWk\niM0GGM7Mhufi44vcQJqKZkOFgeQqT7Phs/j4RW4gGWaDG0hoNiBIy5PPkoPkbTYgSFv2KkAS\nzAYNJMx9ASS72VBlrZ2bCMwGDaRIzAYNJHezQb8jZRcTgEnWNDpI9yXU8TIb9gPgOxzuZsP9\ncBz+82c2JMbH86E/KEh3QUMBpJt9mw0vJ55lT7UiPv4L02x4EsAVpBewAiADyfnmiKiKBIl8\nA/AXB+kngJ9c2khuIGEbCUGag4cpbSM9k9CR/s4fMsS4VdpAIiG0kWwgTZYdz8M04jlZhJfc\n20gaSIb8tJFGJz0kAckpO0hUIkgD4geZIA2HOK82kgaSuzSQBNlBeiaZZxttIyXqjTcHSNXl\naxdA+jmdV0ImCGnPjGdvOGcCfGK2kbxA0ttIDpC8n8NXUpDuSDRe8HYF6Vzo6w3SA1CD/n6K\nvYOZdqbP9A/Sa0mXsv8cpMG7EKSfExLSNJCqaQvlr11rtpJCB2l9aurmqIJ0OlwsB2lHWpr4\nTrsCpJ7Qzx9IC1P/Lwog0VPJ/ocI0v1DplhA0nNBBKkjXIP/dJD6p+8iNpC2pn+euZYYIE2K\nj//yCAMp/1NXkPrB6Uqz4SwFSAfH2ECajSldzIa7Em+ygjQW6ghmAyxBkOgK3reCdHg8AGsl\npaUtk4PkbTb8jxZ0BUizXv1IC/NjNshB2rOH0Hb898IiTrPhYztI46uLIG1ZlZYmeIg6SI9A\nrAaSu9mggWQxG9r/LgEJzQZPkGxmQ3dIKrSBxLLbAOlwenp7GJKXV2KABPANsYFEr40Qk5BQ\nqoH0IO6YBKTf6niO3lGRIG143wOkU5VmQw8FSPnJKpAEs+EiONMOUo3UrYbZ4ATpYErKAlov\nu0sDKQZLoQwkb7OBgvSjAqRE6KOFOUH6Kj4enQjBbNBBuieJPVUwzQZXkOLnEWY29LODNAZE\nkJY9ByC0UBwgHWrX2s1P10CymA2NwADphYQEDSQ0G3SQSsZLQEKz4XBGhm5jngjwiw0kZjYY\nIBUCNIHeAPMEkLDAO0Ci0kG61wUkevw3uRwgqkLNhpkeIPUQzYZbEkeRtwE+MJcdBF3O9ARp\nGCSM9gKpqdVsYCAB/FcH6YUadO4Pw2yAVolWkGLovk+jxWcsAyk5CdxA8jYbKEi/KUFK0sKc\nIGn1U8Fs0EHqDRfgrGk2uILE717ZxQqQ1r/oAdJFpeSQvd24esiQxXxKNBt2p6QstYE0CeBc\nOC19lWY2aDvGbtQI0rVYF9NAQrOBwvG0tgkJSMxs8AQJx7ERQMpJ6mIFabwGUr/UVPzi5ZEA\nkkcbqR/01BMhSFgsHmVWty5lG2kYnGBvIzlAIkQAqU4dGvtgSw2kFEyLZVADCbpaQYK3GEjk\nCQZSZ8BS+OzxsjbSU+MFd2pnRoalqkdB+ksJ0qVaGIKUu3azE6QMugpPkKhcQBoB0ImHGCD9\nmvq+BCQywwMkOOQEaT7AbD51P1T9guyOj8eszwZ42wnSaVCVffN4iR2k2vT3L5w120ieIN20\nFrsye4KEuSCAlAUggDQAYKIGUm9+4dZB2vzkkQzSj8nJBRSkx86xgPR5fPzK6INUneVXXFgg\nIUHjyc0gA6k1dP3WmKG31WwxkoJ0ZUggXQC9fYP0burvSpAGARzPQwyQkqGFC0jCrocGEjxC\n8gFwcHg5SK0iAOl1EaSacAcJAaR77SCBK0iomxynyVTlMRvuTh5XF+pTkG5PSNismQ0vAews\nYMfAQfoybRGtItAa1Gc2s6GurGrnaTY0tZoNcpBMs8EFJM1sQJCuloO0rRW9zxlzEpAae4K0\nIK099NfCXEH6WQ5SQ7hLaTboIOUesoHU8QcrSFumg/i2jjtIN0Nr9t8J0mOlCpBEs0EKEpoN\nBkhLUpsgSD2sIOFuyUGqVYudYdFsaEpy3rKD9KAJUpOEcgdp0SysyUqg8Wc2LE0F6AmdAOpR\nkGhtY4NmNpgg9T6MILHTl0dnp9rMBqAgXZL4qLDyYXC8p9nQ1G42yEAyzQYXkHZcoQIpq6UN\npIXGzN8pKfwi6QHSTXSPuNnwYUKsG0jfeIH0dvoCD7NBA0k0GzhIcIPTbIgEJFo07y/RQbqU\nlngJSKLZIAUJzQYDpGcx5xhI76a+x0IQpFuIG0iaPvsoIWGCAdILRrgO0r0mSADlDdIzbYa2\nySAkzhnjz2ygV204yQoSMxtMkGCTHSSL2YAgtYURwsotZsPqlJStKrOBg1TdApJpNriANA88\nQHoqoTO5ul6cDaSLjBlaWXqX7/wNCQliKSdWkLjZ8BpN5wLSXC+QzoIzrWbDrISEjY47kmA2\nyEFCs8E/SOcljE63gkSzYeJhBtLLaWk92VE7QHKaDTaQLGaDCdI1moePIN1GFCB9lcoMBVeQ\nxosgrS5nkJrnkiXt94YKEl5J5zTXQQIrSKyN5AWSpY0kA0loI/0PR5oxQFqRsca1jQTQPGkB\nkbaRTvr7DRtIpWs/8wJpHNQmA3G9g9blaV3AdJAmxzcVQeoI8Lk1a0SQeBvJAyRsI7XgIXKQ\niNhGegdgnR2k4ry8JA2kopukIOHe+gcpgR2WDSStjTQJM9MJUr1XQmwj2UFaOL6mZxtJ0/cK\nkCaKIPUrZ5Da76PN7uRwQKIFE7qNr+MPpK41lCDRXOIv/HmAxF4KcIAUa+QXegMSkJgsIB1g\nQR4gHbe2PwO0J3TnQTpI7FSbIAGCtDI52fx2WsggNePP3TSQGtcODaSvAU4HSMbXytJo4VvW\nioPUkD25ixZIT4wf/7cNpI+GXKuDBE8ykDq7glQtlZlNriC9SWcNkHakpW0LDaTx9/H/bdxB\nquPxad7ogPRU1xmk5MLrqjhjVGYDgtRB208LSLrZ8IwAEpUJksVsEEFayN6JG4aBCpAsZoMp\nfBNFYjY4QLrgFQlIpyQ+oh/fOJz1D9IPWCx0mSBV1cwGD5B+xhVcxUI0kOqBBSSL2UBBamsH\n6T36j67jbMJBwhstgsQbb2GYDVKQ/kOzTwQJIA37y5sgodkAFpCqCyBVgaoWs0EDqa0VJM1s\n+BVgrhykb1xAgj78X2t3kKCNe2H2C9KB955HuSQqXfIlrR68f4czRmU2yEHKOhFO1syG6zWQ\nsnraQOrcA1rfEBlIFrPB1Pm0pjMJJ+as2eoFEiRJQGoIN+rH5w5SyUjsY+QPJECz4YfExMfd\nQfpGBZJmNmxLTc2Rg/SuG0hbMzIOO82Gj+Nj7SBt05tY7iDdqgIpd44dpBgrSLrZcFrCowZI\nzUWQqrABbAyQtsvMBgVILcsWpMF1L7uKyi1VWIOfoNmQKoB0kgESrau01cwGHaQMEEEafip0\nOYEFiCB1edMGUlxeCYL0wpUiSPc31kHiZsO9WBe0gPTCCG3qrd2kNQwTQaIZ/2HkIO2ip5yB\n1MsK0j2JZ2rLiiAlkewrWN3dDtJ6ikFaQsLPaDbAmeOnkL0ZnaQgaWbDfID7x09DkF6+y3FH\nqm4DaeAFWJSfASgwzIYe8wnZmtgtNeddfiYIghTzPgOJth87D0z5m4P0fE07SIV09aNVIKHZ\n4AmSbjY0hFF5exlIk60gxbLvlhsg9QrBbNBBaiWC1DbqINXy/NhQeIOfEM381UFqKoJ0AiZw\nBYnez7udyAImCiDBABtI+N7Qp5jRgA/wZ/N/lAOjjbQb+xWcS6wg9a6vT80ipCY0YiA10LYP\n8IoB0jksSANpoA5Sv9RP+OE5QSqeZAPpdGOjDKRhRq9yEaRLCS0WcCc4QMKa0Ae0vLK8aQsJ\nBPvtiSCdc7OljTQfi0fHd2ja5uAACSWC1A0DEKSV7aAabyPBfWzHoE47fiZugVaP8AUZSFSv\ncJBu46ECSPjc8yGAN/+xgHR8RwtI2EYCKUhZxzGQMIKD1Bp6MZCq2UFqTiQgjf9I3kaqnfKU\nedr78H9tyhakbp7f/Qpz8BOtYhOv7aYVpMeTZ3wMHiA15+7AQyGClIAgnZ2c3ISBxJwaO0hN\njCkBJE0WkE5hQXaQ6J2RHd3eM+jsiRaQNoEvkHalpS1ygITSQYrpzVZnAam2BCRUxCAtAFrM\nLSDFaWdCBOlq9t8B0qrU1L06SMfxe7gAEpU/kJZBKCANg6pWkKC9HCQGty6tGNa2gJRXL8og\nzR668kBhodtYR5LBTw4UMC2ZiZ2ji6U/+amWI0CQ6q5n1R2s2nWHy/+L+76MR+ogFRcjSHVZ\natQDOkjF9FIyoPgVHaQbeDADiRV4HaSfarMAeodZtH2/BlJxsRykd3cXU5B2CXEUpOktcOJ1\nYI06YC8hc5BYhZCBxA4wRyspgLeu7uygOUjFxQhSMRbNHsaKP0WQbqAFg6abzzh9Y4MGUn8G\nCOoecj4DCQs/TaeB1O1cHptAvqe/FxcXW0A6E05NezenmKadTf9qwMnvaCt7oZjsi6+G6you\n1kGiK6UgNcarECvsoylIf+IxXLx5Op0dyzrh6yAVjzRAKsQeRlSvFBdTkIpv5aGzX2lC4cke\np4FErxaILMcAACAASURBVHx96b+HrSAVT9RBKs7XzIa+8YMtIBXn031gZsOOYgTpifrQHHpa\nQKI7rlXtiov3toYYmmNzi4t7YccRJOIEq9lAc7ComJWoB0EiE6Rm9O9aM6KNW1H2D1K9KmxN\nLomcg58cSJupKbOIFGZKf7Jf5LtXV9tNikbtNayyTo+xdVe4dCqGfsQj3+b/bs3M3MqntOKe\n/DX/3yOTlu/+mZPYCz6vkcJLeXA6fq0AyzJ0xP44tNigy3kCu/DMytzCQaL7cqGQj42NqVcy\nM2tCw/lCHC0iD7MtT6Z/7VnQ4iIOUiH2moP6tG7QmR3gT+ZSp0J3dtBr6fRFdGoLLRaZRTOY\n2avpxaIf8JpdDdPRDdIqx6u0MLw2lEb1KdQ9iXsKz6TYj8Aziumw3L1D//jTA0goxLJ0UWbm\nFQhSH8Jro93waL/MpHvTkW0t4Q1tZRMys1gd9ni6qjd50JmZ37zXV7uynYQ/1z/NTkBVOC8T\ny+2IInIvaPk5qjDzKmg1Qd97DtKLmZkjoNU9J/PQ2VgdhZUjKUh4+Y/F2yPA7VaQMm/HBj4t\nXo9lZn7Lgqb3gHOLEKQ7OEiFmZcDW7zqJnrQFKTrq1KWT5uCgQykIdCERnCQmmZm0stJTDt6\nRcnM7IkXTLzMtPnb2OAnFCRad9iT+SnOJYNEH5NrgC3GisJAM6KlW1H2/zWKz9fvQLmlcg5+\nUqi+I+3g9rFxR2rC70hxDKQ22h1JLyWaRhV/chOf0p77+LkjsROv35Gm8ggKUtLcvQykXsvn\nr5Tfkd7aFfIdKZ6CZLkjoXr4vCNhwXhg5ODR1jtSku2OdDGgN6XdkRAO7UrE70g94+N70xuP\ncUdqjd1xfi9+Wd+QcEdaxf5b7kgP4D/sCAfs7QLzjrQOr3pjWYNHywnxjlQ7hb+MwO5I9fRT\nNvtu/O1P70jjcM+Ud6SdP7Og6a2gMbkD9DvSN+nfstoVBWl3LrsjARYS6R2J1giKi2lu4XL9\nv/+oq35HqnmWscGv/NyRTtLuSCjhjlSlQ8R3pJaqdCSMr1HY2khNeBuJg3TCqXD5x85jHEVs\nh+5sI/3qaCNZQHqOR+CjvpG8jdSzG3RrJqwyojYSLt7ljVbtpqVONZeqbWkjfZ1Cy0BsAYIU\nZyR5P+879v9B7hy/69FG4iAR3kZC1eP/eBvpbM0L1EFi99csMlbfELaRmKYTDlKdUqGNNMFY\nhF0lsI30X0sbyQRpefolBkix2klkbSS9jwjMZrZmK4pTd57IZxupMVQbibdTDtIk3kOeTutt\nJMCMs7eRsvi1sCEhOkg9afVAayMJwjbSbbI2kikrSJcJMdVcy7JfkL64YPGBkhLvz1KH/DWK\nsgFpgG+Q+hogtRFXaQMJ+ovbl4FUihsQQRptXcgG0k3oldCyPcN6JI+yXxtIQ+j0pb/oNy6f\nIOFLiXDCPJ8ggQMk1k3aAKmRC0gj6WHZQbplmQWk1uxffw2kGP8g8YbELRaQQASpOtTug/9N\nkLQePgJIXbAoSUECb5AmWkASFTlIDXnueCYN+WsUNrPBAhKaDX5A6usAqZkDJHZabCDhk47e\n+xUgvVvgDyT8Z4BUB06MHki4mv5pehIXkIyqnQYS11MCSAsFkPSK12VDtAaCAyT2FEgEKZb3\nbKAg5dxo5IQMJJjkARJwkB5xBekq1i4zQeJOoAlSlU3bTZD4SrxAYg8aHSB9owbpjDIEaQuX\nK0NhfY1CMxt0kBqLILXu5g+kxlop65HeVAMJHCAx2UBCnbNdAdKrWwm9up8vxJ2gBomiPBr9\nBUEiSGcl1PEJ0jQNpD4WkGoPcgOp1U48HAOkJ/jjMAbSTxKQOutWR6lRN3AHqWddDLyP3GXs\nLgdpuD6rg7RvqAqkiS4gTSQdeZANpIkGSKwfvRWkGDtIDVQgfWYBaTRIVJYgvc/lkijMr1HY\nzIb6HKTYkO5I8Br/x7I1LjSQzt2rAOmmb0l1Bo+oRqxhgxdovpQcpEbiIhSkLglPcpDw0ZE/\nkE4GuBArdUkWkKCDG0jcrTVAeoD/YyDNM0FqorfLOuslPmGb+o7Enz3X6GkBqRrUHaLPaifx\n6oFaBQBlgqQ9q2AgXWgF6f14BIkucyPh5g28aAXpIQGkGB2kavxgOUjNEKS7eQrlHekrC0hS\nnVCGIPXt2/eC9nHDXBJF54EsVdx69o+C1K4pnH+q/Tjo6ds2whZyD//HHNcQQerbnZ0Md5Bg\naHIVcKiqPsHsOxOkoXp441G2JWpDi+owlnyAjQ8ECUuwC0hDOEgPc5A4xAbJHe7RQfoqofZx\nLa7TgusZGwYXkIQ2kiHTes/VQWq6SAJSQyyX52gJzMUpSLFQQwaSIRMkXQhSDUsOV8VcYK/R\n3Ei0YUju9QGSEZDRCPeXgnQcDzBB6sZ2VtFGkiquDEFClU53fjSYK8yvUWggVRcOYT37l8E6\n4Z7e0Hkko563h2ggxfAc4Lk0tE0tzYYzQapxmxMkXvnxAOlqWW7G6BP8rqOD9B+jPPOuFIJq\nY301jpcovTODC0i1EvR5EyTzStNJA6nGGeb2BZDwZtNAn9FukK4gmTdaAyT4VAJSbV8gad2q\n/IEkSALS7aGAxPdXBhJXOCBVG9+4TEEiB1u4JArzaxSa2VDN3NG49exfBrvahw9SP+Px0z0p\nRnOyKrtjJEwyF63N3+L3AOlKUEsH6WIzKHog1bWm0UHiBUUHqaYejSAZ71VpZZwlXSgByXzu\nnDtZn3YFSWPVHSRtR32AFAuiTJAuzuFtTjtI9/oAqdH48RqfSpB0s+GLfuCmKlgky/KO9E5j\nt1ThfY1CMxucIL3KKhT+QLpRyNE43rdeAKkpXGCkZOcloZWwLC+BPU8B8TGSCJL4DMFNYYL0\nUfxx1kSPsl8bSDa1OlkGkqFYEMrpBULET54gXXqiPsVBYmtn3TYMkDTZQYo1clMG0v98gFTF\nAAnGaGaDDaRaPkCqZjySa8Der/AASTcbpoCrGEiSwhcNkGpR1YCpisShgaSbDQJIsV+yfyNZ\nIfEHUjUhR+PIeDbjAVJ18TzyotyzhXWNwl1gkCw3bSrm7TElSFr9SAfpTPt6HmW/3iBhaelg\nbMgBEso4vi5C4DxPkEx9OsE67w1SjJDSdutkGt7aHtUepCDxXRmjmQ23NrKAFOMDJDBAonek\n0Z4gffQS++cFUiwWqjqymMhBWoNyfBwkMpD0NpIAEuiVdbwt+AOpipCjMpCkt2hNcpBqmZPS\nNpJNxYQ9wBdBamBLUpufZtZP5XRw0aN8454goc8RDkiyNlK5geS2g3zueSNojLbHifoGjdw3\nQUpIsILE5ATJlAMk4Bk84wHZvumqKtSXRUUOEv+Q2iehUUTKAyRNFpC6GiBVl2eIprICya6a\n3FAJDaRzY51prCDFOxMIhT4aIJ1/lV+QxGldfkBCf1ILula7I3VwB4lqj3ONoYGk75w8mKus\nQJo3r9E8qu/rRBUkidlggkRPc91a4JA/kEC4M6tBahAvC2XyZzYoQdKOMTSQZMLbrwmShDRB\n7YRpb7PBVL/7nWH+QJIpRJD0PTJWKwXpL+caWeYeESC1bRvbFnVfVEHSnkVbzocBUgMzb0RF\nF6Rqln+6BH+2m8fCujSQel7olYjtHmsWuYLE5Q0Sql47HzsF1kq+zGyQZswNziARJNPh9wNS\nuyaKBCh8j1gDSbuChQySuFQD8t/2YnDlAomQfiEjxOUFUro1C5gMkLD+LwHprKiCpD1atYFU\n3ZnQSxpI0FKZMjogmQ+EvSWCJDMb/Kq2vN5Wr7sSJEdb0U1WkAyFBJKmhsTa+AkPpNgyA6l0\n1u1X5nxc6p02RJAWansnBak2SKsuzTxBqnKbE6RqstTWOK8kaukg1VCkK2+QxD4ZsjaSX7mA\nBG3UIEmuhFJpJ9pelTfqA/WFQAVINaMCEpQZSK/FP9hgU+NnowrSbMmeGiDh1Ulyouo96Xn0\nMU6QvCS/I4UoHSR1qfEDUox6NWGA9P32iECSqqUaJL9yAclwAsVb1TjvVcUk97HMN6hkIJ35\nE2lKfvcY/CEMkLpL9jRVn8C8lZwor4oaylinL5BiLf/ClA6SWn5A8qEwQIKR0QfJ5UYVjrQT\nYD+50nM4RBYoylrFrlfJQKqzh4KU5/gIsK6wXqM4UbKnli4GYYBkyBdIMa7bCUGr8o8AkIb8\nJ+zNlR9I9gua9Bwer1qZHaQO8mTDFaspI5AueLq0KXmht0ui8F6jkJmj5QuS+3ZC0RNHAEj4\nlDNMlR9IdoVyDk01t8zVc0lVUSCtaNWxeqem/7gkCu81iraSPT0SQZpwms+ErMt2x8g2BmGC\n5MeJDlVRA8llReGBZClC7pk1XLGaMgKJ7P/shU/2uCUK7zWKowWkm/wmZLWSVqpUSvls0lmT\nSXtBRKiogeSiyEwghVxvVZrKCiRPhfcahaxqZ3nyEAlI7hWSqKuzOgkXO7jIQQqr/KrN+dBV\n1iBVqKRPEyMF6dCb438m62ZNO8ctVVivUaifYDrlGyS/jzDKXUcRSEe1pHXCSEG677gLms6I\na33mTW6pwnLtpD2xFPJdHsq0WhCJKgikQCGqTEBq/g35E55179cQnmsnayMd/YocpEDloTIB\nCbaQkrhV7onCc+18uk9HmZqpkwSqBCobkHYQUi/bPVF4rl1kHQoCBSpLSSvQZQ2S07Ur/Opz\npk9nfoq/sp+Pasa477FbREyMZwshxuir4J3OM7dClb9N6VuTp46RTtoDotk68rcu69463+SL\ndI/Uy/vZgleaWOUKYnwfRkwLeVGmP7PSfIH06NSpcQ9Oneo6ZoPDtSvdnMM0f+aqDTkbVsl+\nfgnxdQXJa36BykRBVcFNNeRFmf4smeUHpJ66PJOG+jWKO0M7iPCecwcKXcdm49WParoW5ug8\nkNWgCfFrFCGCpHoUHShaCkByU/mAFOrXKG4N7SACkMpL0QSpSQ91miNHZQ5SWA9kffdR4wpA\nKi9FCaTz8KfZWapkR5LKGqTwHsjerN5xUQFI5aVogFRH68wbKUiVq6uX6wt5UQIpvAeyd6l3\nXFSYIFmdzcCx8KFogHRylECqr05SjoocpH89E4X3QHaM7/1nr9ZEBaTgtuZDLiCF9CZGAJIc\npGrnvOL6SfNwX6O4zf7ymavYmS1bkOyFRzqG+jEiF5BOkAfLZYDk/tEHX6pIkJwvqUcO0s7X\nzou7LO2AW6qwXqMY4ezM7fIoMHogdXSLsRce2TikKvl+x6OSK0ogsU/CVQ6QwluLc5zdqLSR\nNj3XtO7I3xXJQwHpVidILk2Y6IF0hluMN0j+elWU2cuEMeWLaIggSXcuWiD5HWPSW03VSSQq\nE5AO/XZPu4Yj72n4UPRAGlMBIGkfVn7IEeMN0im+NlVmIFVRDp1jV4xjIgTJQYrpKg12AWlA\niCC57af9ixvhde6LFkj1IgYpuUmT29JLKBjxRw9IlnqkN0hdwI/8ghQjbPlEPz0OIwCpijNI\nKTlIseYXnazXFe2wrUPETvANEt9DtzFh7CD5bFXbFBZIVSwgsexrFDFId/58iP0/8Ev0QLqt\ngkGynBMJSEJ9zg2k4yyfoPALUnXByZjS0kcf0QhAinMGKWU/K3xJASTrUPvaSbMOQekNknhz\n4zmvgeQYH9n+GnV0QPLVLbeBE6RmEYMUrkI0G7xAGhBeddlq2gogDbOQKQFJ+HaWG0iNXxbn\nfIM01CwtU1pIz2pty3cwmoYJUkwZgXSzZZe1k2b5mooCJLGpagGpkX0/7UceHkj9bfPhgtTD\ntTD7fB9JV1RBCtFsuFoyNJuPepHmYcawTdXWchRB2mZpPIcHUpM3xTkpSJJRJqovTzeGlHAB\nqen54lx7N5DMvX7ZGsH58QTJ3cBwAelsI+AvS91O/+61ZZlQQerM/1cOkHimlQFIG3VFFaQx\nTjcsSiCJKXWQ2EDsvbRPN0cNpK/EOSlIzZ1B1QkxdtylaqcGiZV286Zq+0iDHCRLKXRvN1hB\nqquDdI65MRlIj1iWcgWJ7kNMvBOkrvxcVg6QeAaUAUjhSwGSvd1jgGQtfqGC9IEwrYPUGguV\nAFKL3Z4gNY8WSKc6gywgnSktG2qQWJXV/GinL5AsB+kXpBYqkLR88gkSvRfXJeJI+Pw0mCBZ\nL6ZhgeQYQ9oOkqITVJmBVOWdKlxRBek2D5CsIwypQLIP0egCUh0RpEsJnsEaOrH2rD1NKyC8\nuLmC9K44JwXpKsleiyDdKb0aUJCEItM7PJDuaBAFkKq3k4AkmgVVND/Ap9lAQYonfwsBfMBn\nEyTrR0rUIEnafhfZA+wgKQZrc4AUGyWQsvfxmt3yqII0wgDJOMGhgqRd7m+0BfsHqbbeDcQO\nUq+BvJcQL6qhmQ0WK/cKfcLsdEZBaqpXLqaMknZwpiAJe3SxFKRGsTaQhCLF1vlEE7jM/ORH\njO265Q6SpfVUI0ECElohtbWTVW8w/y+aDa0Sn3MHKeZ4C0jnst+u/CsSYYAkGZbpInvlLUSQ\neAY4QUp0L8y+v9iX+dtvv33XMKog3WqcWWOsN0+QvnjIccTXAMt7OUj8ZnMSDwoVpN5D+SMM\nb5DkZkOGGGicDbPqQ0EibbTpKaPp9c/4GJRRbGQgWRuU8TDyOBtIwp1EB+kOs1jG2L544g6S\nZUM13UBao10idJBEs+E5sk4AyfJJy2q0ZkcWG7tkgsSQ9wCpivArqqfzAC4SL1soPyAJNXkL\nSLjF6IH0UNXa8S3h3lA58tlGMnJLDlI9dtxXk+8cB48gNXcDieOpVfuqeoHUsL0TpKeT2Lud\nCpCkbSQLSEZz4Pe1+tFZQBoD9dLw6S+7hBrNNhlIJ1s2LQFJ+CqGAdJbT+lFKgZaW+6f7iBZ\neqbVdoC0kBAZSGIbyQSpdT/8SKYgBlJO8vm4Q6w2x0EaljIV/3mAxHEsO5CENA6QqkQNpKY/\nLhpZ+lx0P31pgjRCPwI5SFtZMgEkow6jgXT3vdY8kYBULc0DpOan8mIr1I16E/IyNkMkICWZ\n9YZQQFpM9AdhNpAasBm2zmtBs4YpSELDj4JE7xKdLMdIQfo7w8iRFvhBXhlIhFyvBcVAW37/\nrMYbZa4gXWLp9RwhSAnPN7SCVB1BIuR9G0hPk834zwMkfp90AcnaPJWCJLal1CDVNECqCtEE\nKS7/8NmkpGNoFBG/ZoMNpHbeIMVYQRqWnr52uTVPOEicAR2kr2nRSbpbBAk/I1+XFb6BDpCu\nZyOPgRSkoQJIFrNB77Cw+SUz7LqP9SkXkO4UQcIPpLLySkESPg1GQeomgMQOiYJESIEe9Pg/\n4AOkj9hEB54lriA9f7Y45xsk0WwQQCJvpQxgK/iMR7WAyzBrowVSFbi2HfBqfIwRrYNknCdv\nkKoaaTTVZHUDDaRaEE2QurxSeva6ne599tzkBdK3zV1Auq0Nttf1Ylerz24rSNWtII2iq5KC\nxEsKlprPmjGQTiXEDlLDTTh7x6n8kmbmdQ4/eN38FUCqlzjSPEFWs0E/6VveMMMeWqBPOUFC\n92TKKN8g9daX74U/XiDFiCANNQLbbmATCpD6zrWCdI9WOmM3a1U+HaQRPL9kZoMIEhVrvP3B\no1rDtRgUPZAeRKARpPrGQekgGbVjhKSO8CCCg6S1iqrS2udgE6STyhSkz6uveaFhi+v88mPI\nC6QdHVxAGtMFS+5CLaw7IZis4+Nk59UswAYSLStykLjZMOZxgO9bKEFihce0egSQMFAA6VXy\ngJGu+QsWs8ECktbyn7xYj3WChDs4ZbRvkPrp/pQSpObJrEHBQdIz1wbSQLdByD8mVpCWpvH1\nVtH3Xwdpgvbm8mBef5CbDSZI83hUhCDFgfXTwxpIWHFAkPhBSUFqi15VHQ4PB0kb4AhBetME\n6TIbSOP4iqIEEtlXfPibdw/6xMeUF0ikowZS+wf0A7aBdCKeUg2kN+gC97HjsYE0mlhBaqSD\n1I79Pp+fnr7LAOkRnpFOkFhN2w7ScTpIw83Vv0qeSdBr5F2JpY1kAUmzvl7K0mNdQHo5aZAV\npDF4o/ICqTurT3qBdCfLMReQOg5nIF1ugGR7rGAHiZAtH+IEAwkLKwOpWvy6D4ew57L1CvJY\n9svbSCmYjwwk7dbsAOlaFmyAFKsPLsUpsIPUCCy9EHWQMBD3jTeNGEhdqklA+gFz7L50/sTh\njFYsW7pxkB56j6e92gbSm+ReXFHcd9EBKUz5Aumuj/QDFkHa1RkG0quDFaRaVSwgYabbQWqr\ng/TEW/j7PG6Jg/Q4nRrAonSQLhnpCdIIHaSptMajxbxKwy/Rpm0g6fZASCARbcYAieAjXC+Q\neqXjrwFSTbzLWkFaageJ7kyLWA2k14kNJM1buFCbdYJEfsIJK0iDcL8fxvCGhLD16iDhyTFB\nYq9NI0itl/Lo59KXYpAJEiu/p3zEQeoLNUdq6+FlwQ5SryEDxb0TQPoSvc9BLJCB1N0VpLc5\n2XDeNL4CDlKKVgXiIHWyg1RreTRA2v/s4LMGT3N909xdXiDln2QDqZoFpH2JcKkUpDgTJBys\n1RWkZ3bhrwDSAmIHaTNBkLp8dyr0xsqQDtKDafvZHt4ggDRJi7OAdDi39FpzyyJI9TQD8sml\neqwLSMVbpSCNTWJtG/5sVwCpmm+QqifMMEDqHg/Dq8hBOnM87/h22l+aT+0OUjNoKwGpGa2u\nYJVCNxuQDglIL+bz6G/5yWcgsfLMQHqHkMMzAEv8cUSzZ+qw7DBBqsvqY1PJ4+LecZCq4Afj\nF+GdlVMmA+nXpQyk9SCA9GZCjBOkKxhI13KQJkcXpG1tTrj3mXtPaLddxY2h4vl/Ms2ZubGE\nlORIf7JP1MAZofVE0Ofv7ILPTPadBv0upXOnlHCQ6BJjoVZVy3PHO+jfaBqx1AzC0sBv0pO2\n4e803FpzqLZs/H1/0Sl+3b2LglRyGpxxqAQrHFfldIbL6Sk4Se+j9a62k4MFkO7W4mbQCB2k\njvszD1xmbll79gsbn6G3NK17w4T5euycEgMkunp8NspAylu2sQQLMBaT+Yj1RrwQNiohS9vU\n0EG6oDWCdC4WfVpMe7KaVj0YTkpW0omaCN5jc0Do1re0hGZkp5KcRnBHSQ42LAe0QpBarcXI\nVMJqZJdpNbqxhD+IOTP7rwwsyvDfHH4v1Jr1tenxcpBK2sENCNJ8UtIJrsAcmoDhzejUF/T/\na720o6N/z5I12uAnazFdDahx/cdbefTX/Oy/iBtgT8ZewJ/naNhz9H8/qFmigVSLgWS+j1SX\nnfcp5DEQVQVGX0gvredfMngdPaD6vB/FTchSNwGk8wDycnD4t4/x0cS0jRpIJTlVcQW0lfZ/\nAE9pIA1gIF1OQRrAStKzJfdiXtSiZew0t6Jc4hOkGy4uRjguGeYbpJLFC5nSZ+YeIodypT/b\nOkB3dsG5+b/8EBhIDWrBXV2wABkgHeIg0SXGQa22CJJxR0qjf6NphBSkp7bj7zTcGgVJ2y4H\n6T8UpENnQB9yCDurXJXLQRqo107e1xLTy1KH8VjOKEj6o6oZNMIAqSi7+HJzy/oT003TTJAm\nst4w9BxftviQARJdvQHS/lW5h/D1QOxHsRLvobkIUmPcg956fSupDXPtdJBmYlh9GEEO/Yu5\nhk+qHpsL7ORzLT1Em4KdDuW+9Opvh3KxHflSawbSOoy0gTROA+kserzv48SHuRwk7d3U2vR4\nOUiHNJD+IocQJJpDrKtJMzqFNdxZWq9CuoeNXkeQhuPcOkxXA5rk5u7g0d/wsz8dGWB5NB1/\nXqBhSBQF6ZB5R5q7ep5e0bOCZHp3VeCuARSkq+hK6QEV8NrYcA2kGuO1VBSk/Fx60iFtCf15\nPlcD6VAugnQXzefXaXFZHM/avgMZSPS+1GAw1KJH/twhfkeiZexRt6J8yCdIrf5k0/Na+wZJ\nl6KNdA27B0zUqnYdMPNaNpBW7TpivYxW7XZaQCoEXrVbGW8+GTCqdq9YqnbaNgcw05NV7XpB\nEsGqXeI08nbKLFqYL9ZB+kZLPAKqDiITwb1qR6ddqnY52lMf3kaiCHxHsGrH3mB3tJEQUiy3\nu3eDXrXDYHp5RcRixapdnKNqd69RtXtY3xFWtetkHAS9EN8xZAav2nVKmm2p2k1cQvidpDdN\nujzlXrNqp4NEjKpdexgqr9oRdOT+0nx2CtKHxFq164UncQ8/erNqV4W/KKtX7cg7YKnaxdNr\nCiFvG7lbn5b+rnmFrGpnnu2HCJmV0gSG0uVPpOUhhV0kRiAO3Y+DK77UUtGq3V5iayNVgX74\n1UizakfI6qQqrI1UB04dRUG6HZpusFTtPAqzzxf7trLpndF9sU8Hqf/3Bkg0p9vIQWJWjx2k\np0uAg0TIICNrZSC1gTraNgcw+9QC0v+xCDlIbYkcJP5IxQbShdp+iSC9bwWJFR0EaWlzXm/T\nQIpB11UD6bELAE7HYA2k6lKQpuTt9wtSbDyeZQ7Sm3RKBCmdCCARssIBEj47FEHqkrzeAOl/\neMA+QLoIzmQgdYG2aVv4XoUF0gO4pA4SbdS2iQE2GE97BtLTFCR+U+Ug1YGxFKRbZSB1iEGq\n79BAuhy67Nb8xZoaSKffTkGamHBGtEHig0PmRxek/JM4SK+QXRmsWvABoY2Ltgyki2bOwUEi\nwgBp/C20dKT2u9JiNpwLfbWNDoAePxogna8A6QYbSFXtIDGzwaiJv8QvlCP2CiC9sVQOEmkH\nzJdjZgOCdI0BEjmgnVUO0riTpCC9hCnkIPXfZwWp7Z49xA7Szb/7BKk9DV2VfI4B0t2Y7K0U\nXm6qCCDN2TaNLRC3du0+BtJr9S0g5SNIXfWT7xek75J6av5n/YfGf44j+uog0bXPqGYHaduX\n3WwgPWIFaT0DiTSlJ3T854QsyqiObkX3AyZIV+gg0dJBog3S1FdR06IL0oYTdZAIGcVB2nU2\nnMRAuiqzAJNIQTrNcNesIN2SjGGlX7HKB23aTpKDdFaeAVJvC0h1H+IgnZCxW0s8RAeJkkFL\nBVGuGAAAIABJREFU79j/2EEqyiy+1nwN4qXqrJfQP8QAqWfSBwtcQBrHQLpqzp4VAkiFbSHG\nAtKlQ4Z81lkHaYJPkG7CHOv1hnYQFKRN+GqzBaR/CTFA6o39AS75kiUWQYqP1UEi5CUrSLpE\nkD7hdwOIYzEUpHcaWkCiLda70r7Tl5SAlD1VAKm6BhJVV97tpD49qdl0dtaQugZI69buwhQm\nSCv27JCA9PLdBkiLDZAK+Y7EwYN/pH0vgETbSPXiL6AgDScGSHVOg6bRAOkUXYrETnn2bPg0\nbZ4NJPJn2hwOUnYRJrmMXhwcIF2Ibc1bnCCtONzJAtJTSpCsd6TTCQfJHML8Oh2kd9jzxCfv\ntYDUDLoeyj4sglSDPZYXQPqXbFwsgnTBLQZI0xlI/5DCDQJIdGNVLCDRGlRRNx2kL+UgvaqD\nNL27ANI9+kFQkHbtpP9rwe0aSJPtIJ0P8BhPLIJETg4JpK8ZSL0FkJpbQKLZPs1ccmZ8vB0k\nssoAqVFiDRGkLhpIu7exgI4GSNrKTJByCmUgHXjWAGk1B+l6ESRiZnlN1rOhCyFWkOreCAnR\nACl8ebaRqChI8fOICRLB4oYg8ejLaHbJQZooAYncQWu4pYuGDPmXgfSKEqQkBUhaGykmaXte\n3gEHSL20NpInSIS1kVppII2Z4gAJ5QkSOd0TpFbPfa2DNCPRAGnS+K8sB0GVvXanBtJ7EpCe\n4IkjAOkvBtIwAaQJYGsjTSPWhW0gbTFASqbYS0DSxEFqmpj4iRZwY9LTRGsjEROkz9L+cYLE\n20haWpQDpKuPVJDYmVKB1BSP1gQpIeFRGUh/sPLK5AHSwdTUrxGkiUMmO0CKefIsJ0jsDfsi\nB0ip6XgJuNYc8MsdpFujCFLvhRaQniF2kM6zPu7TQSJasdBBOtEXSDx3wwPpSb8gPbt2LwZQ\nkF7Ky/cDEj5depTYZIDU75H4+CHx2OizgVQlZb1fkO7iPtARAVL+Xg+Qctn3/wyQeEVFB6kq\nIV9dcC4F6XByDReQijP+zHIBif6uRpDIrv0OkGLJYAGkGzxBomWQmQ3GoKwMpDop20SQtjGz\nYZIAUiv+3bfprML4D7GYDTKQStbk7RNBGkycIJ38hgnSKVus2aybDcQGUpYFpMk8RZgg4WuF\ncxQg5buD9B4P+JfnrjtIBezzQeTM+BPcQNpWREGabgTZQKpGyHolSFcwkGirahaxgFS0dm2B\nfZOmKhKkDbkeIOlmgxtIZFcm9nQkjV1AoidupSdI9KSu3a4AKRttfy+QmNlgBak5jddAejJ1\nD8laYII0KOnlKdgtjA3Fvigl5WMEyWI2yEDat4wQK0i7HrSDtICYIJ1my+YZQ+7YpI2jZgdp\nmAnSJJ4iTJAWAhz/tQKk7UqQ/rGA1Apr3qiuMCB9KsDFmtmAut4NJGY22EGaccgEabESpIEu\nINk3Z1VFgrQjzwMk3WxgIP2UvopFiSAVrFOAdGCjO0hcW/ZKQBqdMMBIsA3tOy+QmNngCtI6\nOsnNhkn6jpkgUX3mYjYUDRnyP4zvB1VpI7povR0k8l9aWfwDU5ggre6mgdT6UmdOM7OBOEF6\nVG02aCD92FkKUj8TpE83KUDKU4K0ygDp/6wgXUl+ZCBpZgOC1CYj136UHyUlFTGzwQLSDxkZ\nRcQEabU3SA11s+FIAgnlr42kSwSJFDKQTowfx6KcINHyowAJ5QDJIS+QCLaRPEHiNSgRpHOT\nLtHW/JmtjfROqb4xrn7QU5sajX2eHxdB4lcWEySyjYK0503MBXd5gPSEkIyC1Op8K0hsx5wg\nJZsgfUVCbyNdZgVpC8/dn5KSNshBMnQ9dHA7RjtIGfj/5fj4fRwkRRupMRvYfMbRAtLGtbwr\nhQ+QdJU5SCVJSR8+0TYKICUba87PyOAd6jWQPiFuIBFC10CcIB1MTv5OA+lAaupyvJh7gbQx\nPh7z2AdI3e6Ug6TXDTRRkLrgXVsO0t83KkC6zwpSYVqa8YnV6ILEJIL0+ZAhxTzUARLd6d+O\nLJDczQb6azEbdIkgFW5ygrQ1NdUcVfngdhVIUrNBVB421MSyvcXbbOiYcJYdJNFsIDaQmASz\nQQ5SCTMP5CAxaS+IoFxA0s0GTTKQJgvxZ0OHtzSQPsjSwu7hINlWnAz89FCQPtuOIL10twAS\neVNhNthA2pdvRkpB0swGD5BsZsP61FTzi62i2WDKAdI1DKTnALAoHREguZsN9NdiNuiSmA26\nBjmKkGg2LExfpIWKIFnMht/S5jpAEs0GJjtIutmwfAIAK6y32UESzQYiA0kwG+QgodlggJTU\nMByQNm20zMpAmiTEnw0XEg2k9XrYKBVIH61CkNY8qIF0OC+viPw4ZAgrx25mgw2kXOHjqVKQ\nBLPBBaQVe3bGx78ujxPNBlMOkAYxkKYD6xd3RIDkbjbQX4vZoEtiNuhygsTMhkfW7raGupoN\nqH/T51oSi2YDX8LFbDgwzQ0kbja8np6utffZu3aiuNlwXFqaG0hFrDBrIGV0doI0/7zzVmqT\nLiDpZoMmD7OBSQbSGBVI3GwwQLLIzWywgZQvPAATQMKKvsNscAEpp1AejhLNBuFgE/EGZoLU\n8rm1awuPLJBQriBxhdhGsomC9KI9zLWN5CovkIjWRnIHibeR/muswQESip4pkumrjSQDSZCi\njaRpZnw83bWdKSkfsIO4JTHZ3kZygjRRBRJvI3mAtD8p6VNLqAMkUQJIKP9tJHeJbSS7DiYm\nss4Vugl8LIF0KC0ty4zyC9KdicMt8+UB0i2pa4w1VAaQDP2mHUSxHKRuEL9VD4scJIciAOmp\npOGOJZTyAklXZQDpeVlgGZoNOywrc4LEzAYHSKLQbChITc1yTeDbbHAHCc2Gj4RVOkDiZkNd\nwh+cq8wGKUi79+pT/swGQwJIVrOBg7Q3z1gxMxtSU76yrcBhNshB2ocronllDWUgnZO8MDV1\ntZZMbjagbGaDq7YVuccZZsM77mkaw228GlwxIL2OavC6pJFXhmbDasvKXMwGT5DWqsag8DIb\njkv8yzQb3EFCs8ETJG421NXmXM2Gd5OSXEHK2axP+TMbDAkgTRKCEaSPkq0DvY8Sd8yQu9ng\n1MHMEmsAA+kFIcDFbEDZzAZXrXC5ZKAYSCt++HGVB2yNYSR34CsGpOtr3jF2bJ2xY50xYZgN\ng5JeJn7Mhs2WlbmYDZ4gbdnrFUskZsPOxESs5yNIrCeOh9kwwjQbPEHiZoMHSEVGO8UA6YuE\nhHXCKnYYF2p/ZoMhASS72WDXGBVIn24i/0tIWO8OEs0ra4ADJBezAWUzG1ylNBs27fdcvjEk\n866KGkj709LWCafHXVGq2n3ccyFpK4tQtZG+PtMBkigbSD+moO/zMG8jWeW3jRS6JjqL0CXQ\nJUPfmhtIetosBUgoT5BMGSC5KnptJLskuUBMkP4dMkR7vuAOkkON4h+2giTKu40Ulh4yBu5w\nl72NxFSOIJFNAx9rJQtXgUSGhgISVzmD9GvKFHvQJcKn22Qg/S8x0WilHxMgmQoBJOaIV1aQ\n9qxde0gPLE+QyOHpV8uCVWaDK0hSs4Hr4WiaDZ7Kc+k3b4DkYjYI8m02cLmaDSg3kEyz4euE\nhH8d0WGZDXbdowLpIK+XuYPkMBscIJWH2bDde9htw2wQVY4glSz4Ytb8EkmEymwg9yTgGBOE\njcEngiQ1G7geLl+zQaLpyU/yCRezQVDWprS0HGE+P89Gr0+zAeUGUs5mR5BVIZoNC9L/diT1\nNhuo8rj9EYLZ4ACpPMyGlfnuCYhgNogqP5DmJnS88spT2v3kjFGZDboewoFaRJCkZgPXw+Vr\nNnjJYTZ8kHyfNcVG1TjPaDb8mfq2NufPbLBph+pCHaLZIJO32UC1fxP7F4LZ4ADJw2zYHA/X\nl6vZIKr8QOrAHsVkd3PGKNtImmYkdot+G2n/+PF/+Nt8BLKCFKkibCOFKB0kkpfnUQCZlqV9\nIgkttzYSaQW3+F+vXCG1kUSVH0jHs0tiQWdnjF+QWCeoaINULuIgRWttFQRSuEqGxrZcDwmk\nPYmJH7lE2UFamrHeJaVvHchTNrEqGqTU46+f/PjQhNecMUqzwdDq6JsNir0O32wwZJgNrim8\nWr9MxZZ2mKfZsGL8+E3eZoOLVGYDze5D8hSGtshawBSkFvpkOGaDTR5mA1dkZgNTJTcbNqZO\neuRVoalIDq/JYvp15s5Scnin9GdDrjj779MpmcJs5j6cQpA625elINGpnVmW9V0BsNyaLm+l\ny3aNn1XbvWLpz7ps7xXsPJh5cBCCtMk1yfJ8xTZ2LxdnKUjmbB/oSaf2LhOX6AiDHWv5d7Ni\nGxv/lUdQkGaxqcOZ+xR5tWyvLCIZmumzu/j5uBviXNZSmFmk2Ma6DeZsLWhOQbIl2bJacT5K\nV+xWbGNFnucKGsPIlY6Ie6GOartR7bRaKly0Ds79nunrmf8Wk6J/pT9b81wi8Gf5fpy6BOpB\nR3vsw1CFTuWvsCxxOY54bUm3d6PH6tlPVp5XLP3JXeW9gn8LswsvQZCWuSZZsVexjb2W45jI\njk2b7QU96dT+9eISHWCwYy0rdyi2sW2lPIKC9C6fyt6vyCt+PuwRydBEn93Nj2MUxLnnlWIb\nq7aYs7WgGfS1J9mZpTgfxTl7FdtYscdzBW+lfuvcxr1QW7XdqIKUJUm7Nc3/8hJdBu1TP7UH\nHrNtJFRlayO1sIWE1EbykLRqV0Eq1weyVCU7nGERgvRP+nxnoBSkNwKQQlcAki9VhgeyXiDl\ne7WRc6WNWyap2fBvaqrtUdvRZzagomo2zIuP/5lPBWaDrgMVaTa4P5D1AmmDY2QyQZnuZVja\ns8Gp/JWKBOH3bDBk9GxwTZGleqa7x3Ij9ezZgIpqzwZDpZmqa8qyfbJQAaRwejbY5NGzgSuy\nng1Mip4NlLSK7Nng/kDWCyTPB/LZ7pcWac8Gpw6oSk80eza4pvDVs8GUZ88GVFR7NpjKLlYk\nWC89HwJI4fRssMmjZwNXZD0bmBQ9GwjZ6+zZsCr9J9V2y/yBbIRtJKm+G/9g9Fcato7kNlLE\nKss20jVpv0RlTeWjsn4gWxYgVS5dCy2SklQVb9+yvLNxR+JIR4JjB6T71IkqkcrqgayusjAb\nuAolHqFF5WY2nOyVIkSzQaIyNBtMVUKzQQJSBZkNflTWowiVhdnAVXnMBk+QQjQbJDpWzQYJ\nSBVkNvhR9EBKlIaWhdnAVVnMhnlp33qlCNFskOhYNRskIFWQ2eBHFQlSoDAUtJEqp6IH0gxp\naABSlPXceOfLJhUnJ0g/p0yNypqPXZDkOvrNBkWKaJsNMlUms8FdgdkQiY5+s0GRItpmg0yV\nyWxwV2A2RKKj32xQpIi22SBTZTIb3BWa2fBmqqS78jFhNsgVtJGOajnbSMeqApACRaAAJF2B\n2eClwGwwVN5mg1SB2SBVYDagArPBUK6quRiYDVIFZgMqMBsM5asubIHZEOjoVNBG0hWAFCgC\nBSDpCswGLwVmgyG52TBr/JP6ZGA2eCswG7x0rJsNggKzwVuB2eClY91sEBSYDd4K2kiBAqkV\ngBQoUBQUmA1eCswGQ3KzQVBgNngrYpDWumrh3+5xa39b4RGJWjpPkSDzT0WCtX/9o0iwYLEi\nwarfVitS/LFMkWD574oEK35TJFibsUiRYFGGIsG/v2UpUijPhzK7V/22RpHi74WKBIsXKBKs\n/X25IsGfmYoE/8xXbUOqRWUM0r707101+1v3uO+//s4jEjXnG1WCrxUJvv/GawdQnnuI+k65\nja/nKBIod1O9DeVuzp6tWoUyuyM/H+rj+Fa1m8oE6uz+RpXgW9VxuEj1bcgIQQoUKBAqAClQ\noCgoAClQoCgoAClQoCgoAClQoCgoAClQoCgoAClQoCgoAClQoCgoAClQoCgoAClQoCgoAClQ\noCgoAClQoCgoAClQoCgoAClQoCjIH0glC76YNV/26lfRooWBAh0DUg214wukuQkdr7zylHY/\nOWO2zvwzUKCjXz9E5cW+Dln4m91NAlIwZkOgY0HRedX8ePYufUFnZ4wXSJ6v8Kve7/eRohwS\nVI5VqBMEWRHFnZAqOiClHn/95MeHJrzmjPECaZPXsB8rVAOU5a9VJNi7RpGArN+lSJCjGmCl\nZLlq0JDVqoFJClSV6wOqESS9MxKV6zUUJ6p0uWpMkCzV+Hx7VAMrFi9XjWu3TTUS4Q7VGIBk\nlWocyzWqcWB2Zau2IVWUBj/ZmDrpkVdlRxn+SKuqEX6OlpFW96o4KVCPtKriZJNq8MbSTBUn\nR8hIq1kqTlapRiraobpAyxXNUYRKxYwqLGBan7aH/u6W/ewYmXRxnwsvu/gPaezmfeLss0Oy\n5154/oX9B84xwvZsEZb45aIJjrXs2S7frvmzbbdXLP3ZuUObevaS+ZuGPkan9o0bOuDCgQMH\nXJGFEasH9+07zXsbuJee29i72XsFe/ZuVR3H9jzFNnZtV2yjYOs+xTZy9yq2sSdXsY19yuPY\nsbPg/ctHJj3pui/521THsW2PYhve5+P5C2/I2aLahvRnbRRByhLSFqbNVGkScJ0jhL19zzuy\npB/EwrBOLHEn+bp6AExXbjB8fRADfUYDpM6cOU3baRiM4dfRiSofluGGjzk1wrx9oKK2/nEV\ngNvdIt/u0f9jj2VVrloIIJWILYoD/I60ZOZuRFb2s/UEXiQHCmFD4AZtKl9MvAZgQlOWONFM\nnG8ulhIH8LtjG/vk2zV/8j1j6c8+bSoHIGkYwKLdu+fqIN1Br/N5d+LUxsi2IR6H/CcKx1EO\n2wjjODYNutMatm/1cZij11RUXs2hG3/ObRvvAPzqvmyU7kiuD2SzZrovNJAXyYvMkOIm0Fub\ntJgNmRSkOJa4uxEmmg2n0piR9tVH0WzYxPf0L7K5kQ7S7eSf2qcOxynvdlRgNuhymg2fAFga\nuts23sTy9gy3VZS12TCWbvypbJfIswCauI/jGp02kvsDWS+QBvEi2c8IyGsFcKY2bTEbfgYY\nwxOfYoSJZkNHGlPd7k5E0Wz4l298LnlX54hy+wI94zjl/bGIwGzQ5TQb3gZYIM7nbujGM3e+\nyyrK2my4nW57nJvZ0IxGLnZdNDoguT+Q9QLpZp5rfYyAX4Rbzh7Rzv8U4Aae+CQjrEQYl5tV\nEjNsqz+kOvVkv8pyO6BdgZbxjX9JnjRAuoFMBGiAU1meq9in8scPq25Zh5UDdxeqbieFqmcJ\n1uyWaa/Ku1Zmd6njOF4D+EmcP3igI89ct0JTpMKd7FVlt+f5wBIZO88lsgErAW4q6weyXiBN\n5rnWywh4gs61vu4RZ8rXaUuKF9sE6Zpa4Xpm+9nT0JSjDaj+Pt/TWaSjAdJVZDR4n/VAKtF7\n+lfWkPY8S6dXzP6QobjxTyURk0/5k9ShcW+6LlrWD2S9QCrgDY6zCNk96QcMSObZ+BGdPGi5\nQr5McQN4l9bwWpuBQoomuJjDNon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Z62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\nrkJggg==",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PerformanceAnalytics::charts.PerformanceSummary(emh::as_returns(jump_walk))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  |                                                                            \r",
      "  |                                                                      |   0%\r",
      "  |                                                                            \r",
      "  |===                                                                   |   4%\r",
      "  |                                                                            \r",
      "  |=====                                                                 |   8%\r",
      "  |                                                                            \r",
      "  |========                                                              |  12%\r",
      "  |                                                                            \r",
      "  |===========                                                           |  15%\r",
      "  |                                                                            \r",
      "  |=============                                                         |  19%\r",
      "  |                                                                            \r",
      "  |================                                                      |  23%\r",
      "  |                                                                            \r",
      "  |===================                                                   |  27%\r",
      "  |                                                                            \r",
      "  |======================                                                |  31%\r",
      "  |                                                                            \r",
      "  |========================                                              |  35%\r",
      "  |                                                                            \r",
      "  |===========================                                           |  38%\r",
      "  |                                                                            \r",
      "  |==============================                                        |  42%\r",
      "  |                                                                            \r",
      "  |================================                                      |  46%\r",
      "  |                                                                            \r",
      "  |===================================                                   |  50%\r",
      "  |                                                                            \r",
      "  |======================================                                |  54%\r",
      "  |                                                                            \r",
      "  |========================================                              |  58%\r",
      "  |                                                                            \r",
      "  |===========================================                           |  62%\r",
      "  |                                                                            \r",
      "  |==============================================                        |  65%\r",
      "  |                                                                            \r",
      "  |================================================                      |  69%\r",
      "  |                                                                            \r",
      "  |===================================================                   |  73%\r",
      "  |                                                                            \r",
      "  |======================================================                |  77%\r",
      "  |                                                                            \r",
      "  |=========================================================             |  81%\r",
      "  |                                                                            \r",
      "  |===========================================================           |  85%\r",
      "  |                                                                            \r",
      "  |==============================================================        |  88%\r",
      "  |                                                                            \r",
      "  |=================================================================     |  92%\r",
      "  |                                                                            \r",
      "  |===================================================================   |  96%\r",
      "  |                                                                            \r",
      "  |======================================================================| 100%"
     ]
    }
   ],
   "source": [
    "df_jump_walk <- emh::is_random(jump_walk, a = 0.9999,\n",
    "                               freqs1  = seq(1, 20),\n",
    "                               freqs2 = c(\"Mon\", \"Tue\", \"Wed\",\n",
    "                                          \"Thu\", \"Fri\", \"Week\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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e8OTexlz/iUUakVtHZeh/aFlLxV78g7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\nAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by frequency”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_frequency(df_jump_walk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kXfl+S+SGCKfe/VqfdKT7m+/Csg5XVK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\nkAABhAQIICRAwP8HlXjvCAyFqukAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by test name”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_test_name(df_jump_walk)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Our Volatile Currency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "usdzar <- Quandl(\"CURRFX/USDZAR\", type = \"zoo\")$Rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AgcHnYWkuTTPt9zgZqAMD6NrOrdeyqk3K9H1b063vuaJArJDb85+j4hvJj0pDp7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\nh3gFq5YNlEfp2h+pzzRlmBebWzas45t+R2nZkEv3pDc+2PfKIW2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ZB9W5E92hRbEeUJopTmlJTr44ID9HcmwnSyXHdkpybPSxItkUP/Ji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\nTkSuQmCC",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PerformanceAnalytics::charts.PerformanceSummary(emh::as_returns(usdzar))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  |                                                                            \r",
      "  |                                                                      |   0%\r",
      "  |                                                                            \r",
      "  |===                                                                   |   4%\r",
      "  |                                                                            \r",
      "  |=====                                                                 |   8%\r",
      "  |                                                                            \r",
      "  |========                                                              |  12%\r",
      "  |                                                                            \r",
      "  |===========                                                           |  15%\r",
      "  |                                                                            \r",
      "  |=============                                                         |  19%\r",
      "  |                                                                            \r",
      "  |================                                                      |  23%\r",
      "  |                                                                            \r",
      "  |===================                                                   |  27%\r",
      "  |                                                                            \r",
      "  |======================                                                |  31%\r",
      "  |                                                                            \r",
      "  |========================                                              |  35%\r",
      "  |                                                                            \r",
      "  |===========================                                           |  38%\r",
      "  |                                                                            \r",
      "  |==============================                                        |  42%\r",
      "  |                                                                            \r",
      "  |================================                                      |  46%\r",
      "  |                                                                            \r",
      "  |===================================                                   |  50%\r",
      "  |                                                                            \r",
      "  |======================================                                |  54%\r",
      "  |                                                                            \r",
      "  |========================================                              |  58%\r",
      "  |                                                                            \r",
      "  |===========================================                           |  62%\r",
      "  |                                                                            \r",
      "  |==============================================                        |  65%\r",
      "  |                                                                            \r",
      "  |================================================                      |  69%\r",
      "  |                                                                            \r",
      "  |===================================================                   |  73%\r",
      "  |                                                                            \r",
      "  |======================================================                |  77%\r",
      "  |                                                                            \r",
      "  |=========================================================             |  81%\r",
      "  |                                                                            \r",
      "  |===========================================================           |  85%\r",
      "  |                                                                            \r",
      "  |==============================================================        |  88%\r",
      "  |                                                                            \r",
      "  |=================================================================     |  92%\r",
      "  |                                                                            \r",
      "  |===================================================================   |  96%\r",
      "  |                                                                            \r",
      "  |======================================================================| 100%"
     ]
    }
   ],
   "source": [
    "df_usdzar <- emh::is_random(usdzar, a = 0.9999,\n",
    "                            freqs1  = seq(1, 20),\n",
    "                            freqs2 = c(\"Mon\", \"Tue\", \"Wed\",\n",
    "                                       \"Thu\", \"Fri\", \"Week\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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da2fVKXKFZqj4SuHJD6btfUvewZnzE2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",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by frequency”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_frequency(df_usdzar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mKBkEJBSD4QkmYIKY4QEguEFApC8oGQNENIcYSQWCCkUBCSD4SkGUKKI4TEAiGF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\nYII=",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by test name”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_test_name(df_usdzar)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## The SATRIX Top 40"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "stx40 <- Quandl(\"GOOG/JSE_STX40\", \n",
    "                type = \"zoo\")$Close"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tEuU7osDDl55ThnUtv46Z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\n3lo0g/QA/Xe1tDD7CtK66o1KNU7+1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h\nNLwFSKNNILG50nKbwPUUpLv5UIhM9xpAUh7OCJCWL9/jE0jT9SCtHSGSkIOkrzj51fVNgKR4\ndxwkXkBUkBokl3ls37hxW7R3vdwgRUx1g7SjMQNpIt9CBeljtlQGMxlEyAXdq/MPiIFQGEix\nbpAqp5SlINViDt8FwkASaefknBlsAEmRAKkO3bqtEaRNmR0sILXVgySZtZaIoTc3iBHq+Cw3\nAqSLGTe7QRrJGw0JuqEAxmccYK0KKUi/EDHqjArSinFs1/dJa2guL8yBrNoJkP5jV9fY02lp\n73MAZCARNvCmChLho4RTkBqnp3/MENq62AySSw/S1Q8ZQKIh/Q0g/VsbbrOAVJmdfTblmXeQ\ntmogJcy5js01P41/iP7dFqQxhQGp0tatY7S3nzlIM9m9QwVJNU7NIHWE2G3EDRIbGlIDKWsc\nqz+vXMQcODdIhF1IlBuUChI9o4/knFZBeoUexQYkwiZF8QjSFUaQ+Byve4YOrURBOjdEuBcz\n+W/jBaRbeQoqSOPbuTuV0pvIXwzprWwev6RP+XnX3nJfJZrnRpAezakDtdKO94Pk9C0mkAjZ\n9icDyT2euI18AylyWqSQl42t8m42EPb7xbLPT7Hc/x85cJ6CVCHjOu4+dNGB1A8aNFJBWp/x\nKgOpHR/kfhrZt1kDaddWPi46Ben1pKRLa9Mq9QtDJ83TQGKT3yggDdFA2lYPblvcQ3m4oJoN\ntdg4iwyko1sXffLcd/uJR5CmidH0ypOv3CDVJxaQOu6l18oR3kDygFZlQla21UD6gS7+YE8E\nPgVxKZeBNAziaegvmZuUeA7SOL7FMKJMgMkKd4MUfiO+kQiQlPqdChKtMz14nqyd0rtcDTNI\nteUg6cwGOUh0OTZ9Fh/dmwV/doSMFCAdWb5cP829fupLI0h//tWI1k2EPlIw2M0AIJu4Haf1\n21JAMk5bNUKMJy5yYgZJpOMASNknRc1urZeNrfJuNlhAWn+M3EPD+1tA6gPNL6cguTKPsk/b\nXLRBoIK0Zo0GEg/hILF1ZepLBaR4EHMu3Zr6JAVpsAEkQhaID6rZ0JcNCTjJkGMLSFEQOYBw\nkD4ivGesTyB9bBh6zW+QyAAFpC6zaWoCpBVHh9iDdFcVHUhutde1kQjZGStActELzBPs3PXN\nE6XTCFKN/2/vOsCrKLr2SUIIXQII0nsTBTH+iKLSQgdFikpTioIFG0U+sVeQagEREBXFEkSR\nKhAFFEVKQCH03gk9IQmQhGT+OTO7926ZuXdvsiGFeZ8nm7t7ZmZnZ/fdnXln5gwl0nzNb7WV\nSC3kRDKIDYTUpmUmIRKDRqRZ+y3LM+swLn1pIdL2VqB7MDUT6V8Rkdpv1PfR9+Q1IhIhGbFr\n1qxZXtpPYDv8iw1GIhVCIh25LCHSzKGTkUjBWvQy4XU8RDp0KCLCs9AwI9JT0azEL/ClLzUi\nVQbPKoD09wAJkTSxYTIZJiBSz8FpBiLdC2Xw+H4UGzQixUVHJyGRKlTyRaTnDSNd7EKzQyKl\nEEakNxtRIiU/aSLSn7oeOfEeuHN2RMQHEfearoRWky/x+jESCd8wnEhPkP+6039dMwjB4Tzl\neVNRI1JbSqTN2ufBS6TbSyGRJsqJZBIb/g9utBNpX8wOPfArEIo1+69PSojEl77ksBDpcKSH\nSMejo1k+OZF2iojU3eM+nzm8vVZEeqVAsfCKMMxPYDv8t5GMRCrM20gSIhEcMO4lEsG1zTUi\nmcCINMl0SEgkbxvpwPhR33uJpLWRxERiH2UBkWbrRGL4CmBpb19EOmgYIG4fj2NzkeeFh0iF\nPUQiC3Ch90vnUZz2DC7RFxCYyBYds2EgrpFKH/4Fxa1EIq9C8KgfCFvcBYn0gEakmpxIcVoC\nGpEiIjpjd1QqSY2J8Y5q7i9vIwmJZAAl0gBgIVf17HlakHMDHoHaoQYikbZg9amdNH36TkYD\nA5HK7zMRKUgnEkO2E6ncyk0DMya5u/SlgUglcN9MpG9GDedEqh0kI1Li+YsuEYkdCZRIBAew\nMyJdio4+YSXSAQuRQqvgcK5oR0TyMQ3DQ6TnHht0VSPSHxER+DxWygSREkoJiMRXFEciVYXg\nXhqR6Hei7eaxY5O0BDQi4cLzjEgmuEIk/3gE6vkhEoeZSLg20d8tmsdSIt3fA7/+jEgTedBs\nJ1LYhfS7SFp9J5dngiOxoRJ//jQinUohh2K20v1NnEikoEak5LMWIjFwsSHNfKTFYG2t5ES+\n/KiQSAMFRArSxIY7hEQKlRCJZJxI90ekbuQ1x0Sq5o9IdWJi2IVxIiGunGZE0pcgNhKpuaDs\nGZGmVa2RaCISkzT/HDuOyQNIpFpQYKBGpPfD4Rl69FQKT8BGpLST3tT7y8UGB0Q6/SsTG8Qw\niw0akV7B3pC1cW0kRDKLDXpfEC50OQE7xhiRtI9fthPp1k8z7jpw9gY/ge1wJDbUAdb40oi0\nM16z60QarBHp9H66WTP2A3Mqh8LDvyfbEg1HjN8oTWyIj4nBBamnljESqb+ASAU0seELIZHC\nZERKi71CHvJHpPesRAoq3lJMJB/OnDmR9KWOz7Vq9jlvtFzYxYg0Rs+qgUjm1hEHI9KZvYQ8\nGDmFmIlENHnASKSM8+cvc8rtMIsNSKRvIyPpeyxxmzf1XytXjvHumcQGB0TCkLP2CzKNMIsN\nGpEIjmE1ig1m/ItTYe7Tx80biTQeW6hGIp3cf4xwItXab3g5u0ek+QX3fli6Qi8/ge1wJDZ4\niFRk1Kg1KDZw6EQaqRHp4klJQpRNKYYdI5E0sUFHHYvY0AZCq9mIdKI3FFg6ffpWn0QasgZ/\n6ERKP3iVzVOEm3hA30TaOnZsPBKpIFkpJlJV2xEJkbxIPkYahHeY63ku/XyRGLwNdwuRmDxg\nJBIe5ETS707a2LH/aETiSBEoA4bUvESK3H/cB5F+GfwUhvxadq+NYsM/c3/ViDS1tllsMGMn\nzhXtwYl0f8/j2lHti2QmEgcSqYHxgHtEIomp6UtmX/ET2A5HbSQvkUx2K5GcgrVYxKhjaSN1\ngDtjbETy0ENKpLJ6G2zz3AUeIyPS4/z3ooiI4zqRQmxEwhClfRHJh7dgGZGs0In0obiNZIGF\nSAxiIplwV42X/aetQydSJ9yREskb0hE+174wv4eHb/DVRppBCCeSlzCHe/Zcx4g0cmZPAZEa\n2lJwh0iZRE4QyQeySKT2GpEqsEHIFhiJhHg/sj8jEp+5+M8+M5FuzA9ECgjZQqS/enq+MCRA\nIiEYkf5HjkZHG6s05PPG2UWk5Ak9mvaYKJtp7gO+iLR7dmsRkfTmLNkTGW4iUvJZYTKIkyJ/\nEQhNbNBRxyI2CIl05kkZkWZpRKoIrfeYDCg2WImEoER6iI8hTOFDjaKTp09nfSZPyIkU5l9s\nsBPpikUqHh3mIVJzSdkYGu4WIlnFBrYINyfSqRRBQog0acVbExuunj+f4phIjsQGC3yJDb6J\nZEOyQf9EuEWkU1VqDhs3rGY1P7q+AL6IdPjE45xIN4fXxP1L59mQBY/YQEiX8M7ES6TTsgYo\nMYsNRpw019z/jo7VfzKx4dmIx+xE2vu4jEifaESqZCUMig1DMbKdSHNnmIikWybRnZIyIhnE\nBusUVBmRLlgHJq/2EEkkNjCg2MDhR2xghdgyAtdQ2CFbkdsoNpihiQ0cHiIVwW6vZ+deFERw\nKjZY4EtskBBpvJxIN9sOukCkPp2woyC1cz8/ge3wRaQz5xmRDA83g0ds0BGo2GCERWwwgIkN\nFHYinRiiEekjK5FmyIjExYaCIiItmqUT6btCFiLd6CGSyaNHmMELlWU9yGCmZkjEBjM2+v8i\n+RYbPqOxO6K+V2q64TVluzs6/IoNHB4iFcf6q9jPr1OxwQJfYkPgX6QGtoMr566WntshkSqt\nZb//qewnsB2+iMQ7Xv3DxTaSAayNRCxE+jAU20gfRPBXz0krkaJkREKIiDQGYNNXOpFQn5YQ\nybRsUJhn4riNSLUYhZy0kci/4UU1IjloI4XDI8nWNtKfOpGq+I/vHGYiLRaGCaCNZEKm20g2\nJIOvKRMiOJzYxweGnHV3Yp9zIoXND/jEfiEk0l+MSDrORkTMM8UJmEgL/BOp7uAbRUTS50a/\n7JnbWbosQCfnRCI4fNYpkVj7570atxqPZSuRJkfcKyfSvoiI3zKTtn8i3dbRXDNdMXjwtSUS\nH0Z1wV0iXbgoJJKtOTsSirL/LogNBjCxgYiIdEYqqqx7eywrCRuRuNggJNLyL3wT6XnUAC1E\nGsSm7rFpWW94PCZNpsSIlBLJKjYQnUjHN4h8aTB4G+4WRY7JA2IiZV5s4NCIRIFEkq6Fkpw9\nYsNaq+nEVUdig384JNL4aYiJ7hJJExtsUeItB3QiuSA2GMDEBsxFCyuR9krv1QGtxSURG4RE\nmnuhmZxIa/DIDzYi9WVEetVOpBZSItnEBtpqOX+AEkkuDxjEBguRmDwgJpJLYgPhRJojiyO9\n11kTG6xEyohNdi42+IQzIjXQEVjixJHYYIVAbOBEyh6xgY1CYD90Ip2QsZLEaU+RY7GBEmlR\nanOAsjj5QkakCzYiDZARaeiDzxOHYgPiPBJJKg8YGu4WIjF5QEwkl8QGwokkXVRIeq+zJjbY\nvkgHUw/sF3z8hGKDT+Rkh6zzNlLRrGVCCL2NZCeS/7iO20j/DR58mFAiNdWiOSTS8zIi8Wk7\nDttIGpGcQNTZqhFp9fRvnZ3MGcxEEreRMgtZG+lURMR8CZEkyK42UuZxnROJIUAiFSkkIVLi\n/v18uoJjIl0eO3ajo4AiIu0dXBaJ5DJygkgcARLptcDOnZNEyh1ig51IcrHhnDYbx7HYQLA5\n2xyqTNWiOSFSnSIoNrSzE4nGOs0qVrHRf9tOIxAbNEjlAUPD/eB+U9lq8kATAZHyotiQxB4C\nidggPj3Au9LzCJGTRModYoOdSC6KDaw56xGgHROpL1vW3kSkAdNxitYe2fMlEhs0OBEbLNDk\nARGR3BMb4t93W2x4MVI8GjDuIG4lYoMwBiXS69LzCJGTRMpnYsPmubeLvkgHUz1EqgU9PVNJ\nfRJpQI0a71iINJvFOpZkS1+DUGxgcCI2WKDJAyIiuSc2kITouQdkcTIlNsgmJ8Szh+Dgl0Kx\nQRiDEult6XmEUG0kL5G29Oy5y1kb6fB+YUWqvayNpBGJuVjRQIm0+j9OpORaJtfUdZj3uW1C\nIl1biIiUVRiIdK2xLKA20gf+QxmhiOQlEsIZkSQIkEjxhBOJ9NanQbdVRMpGBECk9JgYefVH\nCCU22InkX2ywAcUGCZFQbBAT6TAhR8eOPWggUleNSE+nW4g0OYZf+2lpNS1rYoMFmjzwYI2B\nzlMLWGygOCduoZBMig3iapouNgiJJBEbCDkb4Jwhd4hEb++hOXPjBBY3xIYlo7gUmU1iw4rI\nSO8z4ExssAHFBjGRjGKDkUjRg/vu9iQb08tMpIFXLETSffZdW7EhoNQcig3ro//17kjLM3Ni\ng2hKBoKLDSIiycQGQvb5WjJZAHeIFEaiyg0YUnuR3eKG2KAjm8QGE5yJDTag2CD5IhnEBiOR\nCDlvuFUrQk1EGnLVSKQ2XiJdW7EhoNQcig0mSMszO8QG4RdJIjbQT5WMlRK4RaT6O+i5BaMq\n3GgjZQ88bSQTQiFEvEyuEwTSRrKAL2E60NtGOtKz50foHYwSqauXSApZQABtpMDhFpFupm/x\npOp2S14jUk0Iy3ySWSbSs14iUaypUUMRyUXkASKVaVxzINnbeqTd4obYoCObxAYTUNi4JmID\nrb1cMOyYifS03qiwEunaig0BpeZQbDBBiQ1WnF//O9kYJciUG2KDjmwSG0xAImVBbKi/w2ox\nig1L564zWE4Y5wkZidS3xxi9tt8mcvbWGMMl5H2xwQQlNliRtmHBT+tEX4W8JjYgkbIgNjS1\nmwxigxlGscFEJC01EZTYkL/Fht9q1O/WrUG1VXZLXmsjZanzV0gkQxvJBxiR4kZwIilkCxJi\nYqTvoSzDHSLVYd7JDjayWxSRAiBSiiJSnoU7RKrOWnNJgmnu15XYsHS6wEmLQWwwwy426ETi\nqYmgxIYsiA0i5DKxYXr13m+/07fGZ3bLdSU2iGAUG8ywiw0p71dlRJKnpsSGLIgNAuQ6seHo\n9Dden2byVpOWwrAtCgsxXbjRxQaL4XCyJEbCCWlSh1IkhgunJAYUGwSGESg2XJTl+WS8xJCG\n8oD4RLQ5KzacP2PYZUS6nH5CExtSJTk4lijLWtJRWeEcvizLGm24iw1pBzMkpUaOJEsMKYdk\nWUtBsUGY3skEWdYungw0z/TBuSQxxMdJH0IUG4SG4xdlWRNv3By0mmGoX12eG6UhNoVcjpVs\nBkA5H9bs3VSGbgLDAEqknMgQW3Nuc+xhuq2aY0WiNpnfuEmkncawCecZ9s3FWsplyeZxqOjD\nmr0bWrUTGF5EsSEHMsS+SAlX6Bep2egcKxK1yfzGTSKlCaqVcVKHS/lQbBBC2pwViA2EL/qi\nxIbrVWyQd8j6ItL1IjZILAKxQSOSEhuuV7FB3iHri0hnzj8XLhgwnndHNggh7Tu3j2zQiaRG\nNmTLyAYRctnIBnmHrC8i5SyyoUM2C6BEihh1lejr+SnkNWR3h6wikjNQIj1L/yki5VVkd4es\nb7FBePh6FRu8RFJiw3UrNtg7ZDX4FhuEh6+R2NDh5tcER3NQbPASSYkN16vYIIdvsUF4+BqJ\nDRkHRV+xHBQbkEinatT4TokN5LoVGxARwqO5t40kRg63kRTyKhSRzFBEUsgU3CPSVOHR3Cs2\niNuZOSw2+EtNiQ35XGyQIveKDemxoqLKYbHBX2pKbFBigx1KbPDCRCQlNlzPYoMYqo3kDKqN\nlMehiGTGuf3SJXuyFYpIeRw5SaTcKDYglNigxAYlNlgQqNiAUGKDEhuU2GBBoGIDQokNSmxQ\nYkMehWoj5XEoIuUOKCLlcSixwQ4lNiixQYkNFuQVsaFTqBIbjFBigwVKbHAmNpDSSmwwQokN\nFqg2kkOUVm2kPA1FpFwCRaS8DSU22JETYgN5a9QCB6kpsUGJDXYosSHg1JTYoMQGO5TYEHBq\nSmxQYoOCQj6GIpKCggtQYoMdOSI2OEtNiQ3Xr9iwX4qNm4WH/94mCf/femlSa3ZIDP9ukEXZ\nt2aXxPLPVlmc9f9JDHvX7JaeZqfEsnmj7DTy1ORZi10rs/y1XWbZ8o/EsGvNvoBT27FGFkWe\nmrQ85fd6yzpZFHnWfD0Esruzbov0PEJsymYiJUavkGLpr8LDi5dJwv+6RJrU4uWyOEsDj7NE\nloEVS8Q59pXYtcraMmnhSMtTHmf5YlkUeWryOHKLvDyl91p+nS6XtDRrEvydvURSUFBAKCIp\nKLgARSQFBRegiKSg4AIUkRQUXIAikoKCC1BEUlBwAYpICgouQBFJQcEFKCIpKLgARSQFBReg\niKSg4AIUkRQUXIAikoKCC3BGpLQNC35aJ5pcl7Jpo4LCdQCp85lAiPRbjfrdujWotspuiYta\nq6CQ//G7KxP76uzE7cFGAiIpnw0K1wPcmWpenU2KT7rFbvFFJImTJqknqGtlyfEMZCZr1ypO\nLr6ca5U1Idwh0vTqvd9+p2+Nz+wWX0Q6Fic8vFvmVu7cQWlSO2SuKk4fkUXJ2C5z43FA6pXk\nsMwV3dXtMscbGdtl3tbipJ7o5KntkznPJAkyZ4/y8iTnZQtPp2yXPkfS1C7tlEW5Ik3tkNST\nyTmZlzxpngnZKXOlckbqilN+dw7KHaYI4ZLzk6PT33h9mii7mfG0KvMaeMaHp1WZe584H55W\nZR55crOnVentvbBbZpGWJzkr81p6Ofd6WpXmmZDtMo6fOiiLkiF1t5uTnlYzjLLd5SSGQ3MT\n6DZetDkzsNOkzmv2douckJC0umOnmCX3r6KGKW2at23dvsfehKQNnceYY5w9xX+d6PNk545t\n27R9Kynpx/ZdOrWZEf9L6y6rzw7pENm2S6v7V+sxXmvZtn3Pbf1at2ndsWW7ZRee7di2X5ul\nSUnL2rft9GH8S21bt23/ZGTrfodo4L3d23fs2KFT67a/sLinz2ICF17o1v/+f+OHdWzbqvOo\nTmvj19w/ul1kvzNzO3Tu0q5jnyMn+tEsDF1yf/TAFxKntH9s/UMdftTOu+r+Dq06/O3JeFyi\n9mvWg7FJi9q1jezZps3j5+mx8+fE5UI3cRckBp41UbRzJ2XlfCJBYkhIOC0xJMZJs3bqnMRw\n8Tj+WtipXZfvZrSfn3SqT/93Osxf2L5dZNu2zXsNfLxNZPetSX907HWMBV7Spj0tjfhT8Rj3\npdY9e33Vrv3r8QkTO7SN/Iyl91bHSW06/BE/pFX3dt8kvd/pgW7turRrM6R368gR7Z8691uX\nZcKsnWe/Pu/QZ1N8wrlBke2e1K78wilr4JVdlvFfxxMlhRMXLys18Wa/i0TaaQh7eW6UP7wB\nFHf3BAj+NuoOgFZloNKMqO9CgaF3VFRzCPpCGPFx0PB5VHn8V+S7ogC1hmgHw17moaayvdLa\n0VvfZP/Kfxd1K/0X8oqeBHSjQR/Sd6obzjIeD7Qfp1luifo/9r9wEN9/aqh+OoABNM+1AcJf\n5RFvw8N32bNdElpE1dNi9fFbOnkTnxehF1c0BILeeEIvHS9qzGoC0PzJ72i4WnS3rRZnsm7/\nbDYWbgG86R+yA3e8itvio4LAhKrhUD8q6rtGlaaJsvAVfRiCXosaiSFfkeXzNkzBXfhT1QIg\nUprxa3iJf5G2RMUjZUWbOCzNDgPp5kDSvQA16Y9h8Vu1wnoqPqkdwB/mGBf4ryf1Et16ntNu\njamcw3exwAtMBxu8zf+vTkIiQQGPoT8N7EmwOjtRIjvbCjzQZqFmKXeimCm98a+bb24p+lfw\nGMtfXdxv6cl4ovbrdCGA+bdqwW/CY4nicvHkIBCDp3ACMPjIQeBZO5dwgf76UC+PvjeBHU1Y\n0Uyg4SrhPdjNs/abbl63mv1bS499yX7dM5P962xPqV7S0RcAPhVkLYG9q9rXboD/xmrWC+bs\n7mxUCG7OfKkJNy59kaQdsjuj5JEepZfaqSvdHCJ38vLpNv1V/UaQMxEA80zhNbHhlP6VgS2L\n+f+XzKW8mAXrZTpWSXuEfyJVzYH706D99J1yLOaBvbNpm57d1Ts0/kGR0eZok58z77OXJm+m\nsOzdcuQnLhh4mrP4hfvkZi14cZLPxIZ9JWv/S/8NtD/zeLX0L9iz9xoNx75UG7jYsFI3dB3M\n/q2hx6awX3dMtCQU9LL2o8KF3nRbvpGpJcXEhq3G8M9xg1VsmEVNldkvodgwv8minBIb5B2y\nvoj0Fr2eKvhN6ZTRkF+4t7S77KNfaBhvCq+JDTM9gf55l//Xvi8R4fz/NyzYXaZbULQ8/z+N\nlDDfm140aBdPKBZzbwcYQAj7IjXE+1UY7Bg/AAq0sx5cx6LTx4bmvSyMZXseseEZGmBcTS1k\nKMlnYsMX9HNL/7WC2uGWQuk9Y/s6+nm4Y1Vl7cD/CLnIfqxhYkPC/Z6g/PYvoem8yX7Ve9mb\nDL6pbnh9h7ZXQEtsojEPTGz4w3jukO3MYBUbPsK02C+h2HAPtMwpsUHeIeuLSFM8Fxxbx1T2\ntBIUiW8NeN4UPpU/ku94wv32iilahz8rs3vxCQvWUD86rYohzKTzlvv8IA3awnO32PNzvj60\nIYR97epRjg0daolS5wGA9x+Cegcsx+FXduIwKN8f97pwJTFBe7njsS76wwT0631F6sfbE8eG\nRJmPc3JV+t25KF1xJk3qylzKPVlq7wGsoP8awP27DM8xbt6mqX0AxaYRvdo3gj7y/PaR5FTj\ne5GiGd3rQdNhLRyo3AAK6pXhPkshaA85binxYaas4d1bZHrxhTXBb3uKhS1jMG/8p6Ck0ypC\n9RSSJKsUSJDdHbK+iPSV53rnVzYUzrRJjwHcifU+6CaKNoy2p+pVQ/PC4bTleYcn4sPkNRg1\nCOAd9rTVpKTC19gEch//ZFXGj9/7/2mBdXYVo6X/f54ksMTP0o9Xc0J+xv0aLaDiof+Zb94s\ncpU+Hp0h4qTlrgJvbwbDK/PBnvse9EiDssxAM7LMSbHmVrwfNsN66CmApYTE0KryBW95YBE+\nyx6N9bRKOlc7+gIhD7MfS1lMlHPomzOkIB568UwBCFtICH93lS4J9dJq0x9VMdYv9D2V5m3c\nMvS15W0OfS3zhsJTrOkbLcg/a9/KPvrkX8x1wGWS3R2yvoj0nac8phc3FM4Vsq+G9vNmcwT+\n9hiIX6pvUBD64RkIT1yFAavhZjBtd+AHoVzQOBrsJug18lN6NIrsehcrkTAKa3ev6yJBW/10\nn71yBlsufZZNag+A62Ngna4p4S/Qio2hE3nXfPMSkSuvtYR7LwWbDfAFZo/Ge2cT261lyDQh\nHeiR2jdAE/qPkv1LkguGAmR2+EBjaJhCv45L8Vm8NIs1zjoCfEcIfbG9fTWEVW0haNBEQv8n\ne1LT1Z+hhNRmP+Yzwxu0xUOf/Aoz8BkYTejXvhMhXJgtHEpfjljze7UEfR8yVMTjFTwl3t2W\n6Y8BTnVgtkns8/V/gssZgYYLsgtdTo0F03NmZIO8Q9YXkbwf9fsMT2Nh2pztof/OILuXeS5J\nExsehFJ7SMbS3wBuKkzbjP9gwHVY7X2JmUtzHqQXhuEkif7G5vm3GOZjrOyNpC++MrjnrZlD\nhfLQdlYiqzqf1wLfzqtiUDKMknaaiS130CAF4eUI6EjqG4/31+qU9wCM5W/lG/DL6GnO3kuP\nVCkM+DJ+CeDDvCw20Pfc2zu/aQt30Qt8Derh4buwDoeqzTLc4OM+hh69mTUGtZENy+hBlD6f\nJKQcKypfsu4AACAASURBVJ8oJjbQWtw7rWhTimlPbxPaKA3eT/rqpfoe49SqFW9qF9EYD37G\nbVVLQWdj1pjY8CyEpPdm5q+T2b/9VrHhRMdqeHwV/haJDXPQejaHRjZI4YtIX3oeQmPN7iba\nOPbIaIdTSoFHoNfEhpZwH/47xQLUZl/iG7adD8ZCR2CdrQZ2asHnJCMEiuCxLRj0y250g8LQ\nBrwRD5vYweSdqfRlRnhT9BZW/cBnn35maA2F1TugYBHKeRxYVBRGlIdBZN3ARt6m9Uz+7JDb\n6LuQNGWH1hKv2LAeH66ywfA8fWF/yJ66PCs2jKeXUL0kXuAakkDfG/hCoA/4KPZdWkN+olVY\nWvvGS2gPpYlnZANWHbDHYxAhhVjxTNiIYsPTUAY/Q8vIPkB1CXW/QvMf0Ev1IzKKbv/znL4t\nra4X3AysNvhCM4g0Zg3FhoSSUIWwunj1uAxWD1xnFRsm8ZSn4m+j2JCstVmxGgM7c9sasr6I\ntMzzELKCDeEP5WDanB2lG0Lpw/+WHp6LDX+Fwf34P5EFiEDGQN2E9MqoyCGwnlbgFPkdG7Ok\nFn9fMmbOOz65FNxNfyTRNg48xqLrHaRM6JsBcJzwpmgdQm9u6FNoWkkOF72BC+w30ybOYxjy\nBnguBF7FXy/SPPL+whPBTNj99yb8MnEVf+SaXZ7mLPsM0pAf0e/iiaLYSs6rYsN5b81qDlIH\nNtPD9ZmsTd8f/5JTxYL70KozBn4eGnpTW0uDNu2IJXhBF1q/TSU774Dq+M1fQ+LZfXjKkzh7\nHH5k2pJ3DbNx8Pi03xILA0x84/9iW8M9pqylszrhTMKaqM8QUorfP4vYoFXueV3RW9LHS5fn\ni5uxnvhVOSM2yOGLSHv4az5EK7jiL+CWKX/7ja2PoeZY72lNzKvM+DKJC2LS22gI4+NTkSrw\n3yv8PfYyfMAOfk13l6MAgYTNwDci74TV9dVfMNAX2KPFpddqhLSDpq+h6SB9o52ZDdBmxcCV\n1bQXWRm4RdPm6T2bMB21PbhcFPWoI6hoTNeaVeWhmP5EputX80MzgISq8GjWijUn8bH31jz5\nE9bVHqAcrsZk7boQSr8xB7dPoQcx6Nl3vd8Sgg3H4fRl1YfQWvkbNYP4rY3Al+Gp8lXjSRo9\nsA3fTAyNf2Si7gH8gBQ0vApO4pP/Ne8s7MTq2bRwD7ylf91p62snrUYHsYp+deTrEmv+8Qz0\nbfuO5TBtwv1Ofv0ig0vvM6WfZAlykkgp7J0TXkQrujKs8/Nu1v4z9ov38kRgbw/aOH2C7TFh\n9F9CHgEYkUGOdJvKA7F+8FVoxCrHRf7G+ZHu/qNJ4iVZO+pFVqH8RDsHSrd4e7CugxWDCiS2\nIbTASkAQezPR6goKGPV4dyHP3nT8tY5R6weAMJroUBYQa4Pj9cwv1pqzV0DrJlnZDoJSsIGV\nZ8UGQ+eOhu/J4hJM6SqL9TaKz413TU8Nq24z16K4OgtbLpR60I3E0o9LG/ptRKoUQrFH79EY\nRHYg1c5iPWGENWuXuvfG29INbsUjc0OLs8YSf3BCaL0l42/akML6ZiX8pl35E6uZ//TZyBPA\nyuProZrg571Q2tD47mQIvWEjIZTeqWYBqg05SaRj92CJ1SipFV2F3bhty5qz9Qy3qbZeAeFi\nw2i9e4mpz7TZROuB4w3TKJhu/mwdSgFszWjTKKKBjTtoqhGTUuh/wdBm9pTd2jkYPb5nbzOC\nH8Yyu+m7rD39DkEpFn85VxIaaNV1fAhQpWJPx2zWeVGGVITHtXrBD963dujPvDmLFVFWJdr+\nBDSlNf2meVds8Ax19GDcPnzmu5PPQmA0C0Tb6yO9UfRpFA/SpzqjOg33Aa1eMxUz8ixW4vto\n4UqjNLGhIk/zXUJQZU0lUQDGWdzGPPfFxjAfw1L4Xy42FEWdiJCkqjfQcOOL0zrF12QQ9DlX\nt1YDaMdj0VrobbtLQK0Ji01iwwSAj/8B+JQ22m7EO6XRjnx27yZZWRiRk0Q6jK1/iCin3Y7q\np3H7IGsc36cNuvF+LoguNoxglQgEjjM5xWpkywzTKH4K/T+AllXppw73tGkUKODQ1mNrTO4X\nxtP3C0B7mgXtFDEYiH62Yuk/rPQVXUI3PXCgHW9j/Y3dR4TcDjexdloExmEjkdK7336CYF2l\nOm2P9eEspA3nGZ7Mt+RiA/YDd8f9U+c+OUw/omWi86zY4BkH4kFp1gVR5YGCKA4g5mnfaw59\nGsU7eCsb00rfmwDphLajoPnu6nT7uhauBntrHeJpzmQPQVFacu0GGDNjzPNTcCP+a4XhX2Bi\nw5EgeJOZUvgDcRZgLP1KNXoeg2jdnGWhTTpBqoQmGsUGyrkxtD5R/3hvqI3tbI0Yl0vxZrE/\n5CSRLq/Bd047LtndBQ+hWA3PscYxbWPc4LlPehJcbHjeIz/g5dJDyQ8/cTXBUNbpMcA61Rvg\njt7ODIcQmuz9Gi97wO1nwqALfXNpw5PZUJJfWE2R6d7BLejmHexRYAohyn74AXpIq7GwTqi1\n3lNSnt1GbsFeDYwM6/FJ0nA7b84iY+OAZxiVKihxNbeIDVsfXGQ1+BIb0rCh2bOMZ6Av4nvL\nvVqsD3g0pTYNh9c1gQ608hzGunChxTcYR+9+vAOq0O0lfkt+Y4OqqknyzDESCtHtTPbKHcTE\nhmcBzKOwq8Kd8QBV22CQsvxQYfxaIo2xIu8tafoKfA01qU/ugzvvYu/Jiy8vJL/jgK/N0tLw\nIieJxC9nYC1WcMe2pqYHQblPeN2Ftl1u9YzBN3ejP8WbKxS0Oh0meuK28WjtjMdug/I8WYC/\n6c1afZEUga6EPdIIVl9YjDfaMNp1Jr5oe7Dol2qVxCDnv+ZfBNbPZZgRuhngUfocVD2H3SAQ\nfJw1iTga8BC0WRB8CW0Z2h5Iq2LXGr2gLvv/3zpHwY/gVR3m/3R4un2wIUqxLShEUGtcDEFH\n6eej2dXuONINK3X3sZ5y/RFsxwsrUn+1zdC6U6V4G6t+WGME7IdCdLKW62NQlb4EC7JRQ6Hs\n2UpkfQ9MuttoDDlI61uk38hOOIpyEZkEha6wT9kEB8WSk0TKYO2Zt1heWb9pYWx3svYfbZ1E\nPxel1e6qxHkiEBQ4Q1Zp+1t7fGa06NjHo/UyWh6De/EfqgSakFScdYtrg7rZXN1l9CsTH0d6\n6g/FPPqh0ev6aVeMp2EPjmF2506UHO7Ghi1SDGs1nok4tXkc2mgqlAJ82DdhQ8Zq7cklYkMT\nroodDQ3abDYY8ccq3fIHwN30STytXV+4NhZfa9pot2qt6RnVUkufRL/qXeHWmQA3EYIju+/C\nboVgvQk0Fp7GfzgfAApcYi+2tj4v5yNWX+e9+V2Z5W4INkv6w6CYZ3Q5fE9pNOF91txl88yW\nG1N7GEAfbTYR2xzzkeqxg3B/tLwEPchRsSFuAOBIT+y4YUOfKrAxTtg4PnFHD1pZ+xmnPBTm\n44qJLjY8SpsjNph8NqSyuSj8rug+G06+y25XFe+noCQjkjZNgn1o6CNSKqhQV0/j7M+NwJtG\nHug+Gx7Xc6whvihEk+aoO+BLDT9VbYO1ZG6cympwtClbAiXw8jwCTsx5OneIDZPDuL75J/16\nPvwsryLbxIbdwUHb6A1YnEp20ybpDqIP4IbyS/l4HPiAbYuIWGvy2fAohNZhVTZaZtBoCECr\nDR7bcRbuGfb+OcQqzD3FedbwLRuzeAs7czsS/ewpUp9WHE0Yi50QOr7Q7vc61vmOLz+D2NAe\nR+xzbMBKyZe7KUOXP4L7T8gK0IAcFRtODIWgaRmsKzkIy3BuLywlQ+OYVm2LRnreCFxs0Gsi\nJph9NvDuU9ZhavHZUEf/+mBvHd6lCbzo2MO+Ccw4iwMi/jZG130M4L0ubDRs/eoKVklm4O1g\nvbppp//U56N9hQHoe7AKCQa94Ypv3Vq5QmxIwyFuX9IdPoVxCzPYxIZoNsS0FbxMtvXkw9TS\ny7Ae0968ugyhy9m/PtZTIEw+G/hwVBxEeSP9118boGi6kom309YTvdc7AHVQQZ51LMd+RG2C\nWaGY4vAeKY8DLo0wTe+crlXlt7MqD0DHy5/M0d/AsTU9wW4n+IKfjs/KHKasCB44G3JUbLhy\n4NEp9P96wG4YDwyNY1pRaoAztVbSoxc0saE7CAaZJ5huPLu3lVkVzjKCHodqaS/1G9ld5+P9\nGI3JbjChINbYmpkSTtYcDw0Hz7dFz0AG6rntTrWGG/U5Mvrw2Bdw502sUBRktQsEzquplivE\nhkOYxZp0h7X74c8r99Q5aRcbKMueK/fMTfAAStf8Xu38aTKEBH1JMtgzWZLPUha6szGlxget\n3E2w/gE31dMm2JlBP0UP0Ht9uTyK4II86zh1AwpG5YBNvKX1mhdp4+Alc/Bk4/Qo+rAhRVBk\nmIfdeo2HQXHt239W683EsWD9mHA7A7v9XmGTBEKlpe5FzooNHMdoXu8RWmgNtfMZwL6AC2WL\nabMh20MTfwmm4ttltsiCo+e0UrmJjS6I4q8zduSEmUg3kf2WCS8eYK/hUOtBfHn9715ope9r\nY7rgER4jaCcp4tWUCgBU8ncZ1wRsGCL2FPBRTb/GaB1kZvzAXje08rOFZryidjB9yVFsEu1F\nWyX2Ob/Lfy8mr0tjfzT/ktQUhNmoDV7Z9bn8XcPQGwovySgBzF0Hbav1uwLwviWIPi0NMZn1\n3gMcZZ/Ym6FCR9YRiVitBcHa3WBUhiFCSzSkJP3dUOruSEfOig0c54AJKdbDhL35X0RRfDoO\n1JrDLc2gtTwpDdhEXCSydPB++yqyWeZ8vF8FdiRZL3DevGlGjoI2zdV6mne0ITAmC7ZQn7oT\ne6c49L4kFAfJSBw9W8KrUN1AiZoLxIZLX7AJlAW+SuZDq2DeIoCP7XE844tRHrK8yC6isNKI\nzV19iwhhTI3PHu9Hf/FZQ/UF4WklZIijyxkB0OkvgJe09uhNp7QhXAa0MBCpM46gpDhNv3a9\nBzwHxVpjB6zpAvHj9rx3rCe+G9kMT78Og3NWbOD/L4M+q5XB0DheU67LcWyif0SW0uYsExsu\n1rE+wwiLg0gcpsUGK1gdRPbU+mkJvqpeJGwqGgDvDSdE92+C02mafXaQJBflg/A80MWGFdap\nXygP4HjywY35iFqE3rnCZPjmODKpFMACzUjrNaVyXmzYdS9oIx3v1iY8zh6NHaQ2sWGq/ljd\nRlm30pIMNknbHKZ1pSDxdEWT2MDmpJRfRX/tZQNbbhNdSxA848hB5Lv0I/gjzfCNPHPBsfi6\nNQM1WH3uWSOtB5BXNV+HYPry0N57Y7Qg2MZ9WauVl2Gt3AOxuP1ckh0PclZs4P9xuPu3hiiW\nCjp9rF8eS1/mI5nY0Ew0LdLqIBJHvMWyXxax4RNvH9+WYTim+Bh/z/JDensTv+9sYsV/C8wP\nlC42HLVKoigPoCbeoxqvySEWaak1J+xjV5Y1r/UhlLUBSuS82PAjyyA2D8JWaESphG9km9gw\nQSdSeUv/HGJFSDC8mFq94GqJU0eT2MAGQfDvPNOE7hTFeLDgXEcOIuntLEZbNe//1ojnLtJT\nEfGAPgqNdIdfNTStnJfuOPo59AgJ+lhZrEa8zWdSQL03kZwZV7ATarIkOx7krNig/ejkfVMT\ne+O4IkBLnFI5BMUGnGssUCPNYgO7W/xTZBEbUkNR59HiIElSWa1gDD/SVCtNnLBnm0yN0MWG\n054ohsQG8MhP6od0NxyFaUU/jrUsynunmNM7XzTHxYZE/viwQe7esRgwiGT82udLE/08fjIK\nGi7Qg1Mnfr5MkqQ+bc3SxVfApjUSwofIjxJGSUmV+ac1Tf34gmdqErof0LDGEj61IHw8n78s\nIGQ9u8W8Lw/ZciPofSnYoVGGhsDRJ9NIChsreTdWe4uxdzeUfUN2dRpyg9iAmuRvcmsDekk4\nNIr1XR8CNtPED9YBhIp90X79pOWdXgrLT/tw67Nmu/fBIfU+kBpu8RSG4M6k9IGAvO3A/O7t\nJylL2cTzyjh6iONuk1CZQ9AePzap/jPWp8/wCDlZxPLdNzoj81ky/oEqLJe82dO6Oitp/cBz\n9IfmdYiilO3zGzUigTaEufOCT8ntdNuQG2azWVG8eYwiRIFXcWZAt9Kv0icH+86hPVbqKrP3\nPL2TV8nFWB9ZcYdI3TXYLU7EBpy48I/gsAZaU22CImZntODE8hd8JMWxxdsi9teij4CHCuln\nH6A/SX9C6El5FIpdv2bYLJqzoQ89xypCMKtlr2UMbYjzYzw6Ca2EBI2Qfl6ukdjA9QVgc6vf\n0XQqVtDYvi5hGC3nqfkgpLMBnWXtfBjvaSNkOqYmG5fk6HJ47Tk4nRy+V8vcvaIoK4G5ysCx\nPji9RrsJnIVl+E5nCBsxhbmL4CdBU4+MBqzviY3Lg3tGRWiO3oRwh0gx1d6MRtgtTsQGrIFv\n9R62No6PNYTGOIX2ThQbsFY/kthgERv2gD4J2e9qFLHvnI7VO131CsLrZMlaYRyfq1H8zjzm\nhXor902gKuum6sHGGt+Jo2z76zY2QGy5j9TEcFNsuNhRcw/N+lL70wdMu/yWvElU7LQ3rHGI\nqiRvjlejaKb3QLCK2RZxHGerUfzOMoRDwJdqmbMPhSBsrFG7G1GLfTu5rjfMLyxCCb7TAu4j\nW4K93e9YNI+RV6BOuvfig8wTo8xwqWr3hm0eogYnYgNOXzE0vG2N427QAFsy1VBswPG5gqFP\nFrHhKPdXRwJcjUJrCQyTTtf3vRoFE00NHYyrbvvwKzxUnjn7aEkbvp09E0YX4tRzWdlcG7Hh\nJ50ZzDnpLZTw2n6Bzfzjusob9jEvj4Ikp3G8GkWkXp3CLuBCkpU/nK1GsZ7lCIdJxGl+uoRN\nrl8BHvh31vICUIfNrdTa2Lzng3ch0iof/Rgt92q02KZ6hlyZi4+o15GvDy9duUJsuNj3FcNh\nW+P4YWB9d4XPJ7OuGG3GiQkWseGcx1ut1TegMY6t9qC5MJwjrXLpYoM4sV8xckPTYea+KJw5\nbOhkjoCjJr9ynjUNbooNHj/dzGfmDRD6hH7gU95YNCipBqeysqZd+kVZBizjJN7VX+y0btX4\nP0F4hDOxIRmbPLw7RBs7+6UoDuXbQwRHV3JoTYPVbCeY79QyTell/XyeF/a7uvMb6/gjI7Jt\nWRcNjsQGP+jD/WBA+10kFf+/5z8njQr+lYkTaX63bNNzHIK9H7uYDv3IX3rhYJNIUJKdlskT\nuYELPXTvtqGad6wyz+hcacVdlH/sCZwQBFWma8ayWT61/ln/SdiTERAO4ieSdR1pSsl8UahY\n3gOsDVDXCbKO72Hd/9I/N8IQUxTsmdJbKp8CfM7DPibPiZtE2ikI60hs8HO4P6or+OmOPLgB\nL2ec/zip52UWX6fX1NQVgsBOEmOjbV43HWZjJoMy6Hc02PLFwK6KiUSC7BYb/njh+CzPJ6Yk\n2coGJ9YZASFB7GFrGMZ8+Hjdg+yj9SGc+oE3YVLgeZNYFvoSYJ1dDrobaMp+Nec+MaydxQy7\n+ehXfbSQNoBvC99DP9M4KMXc8sZW7Xbtd1yHlzbysOavlgluEilN0LZwJDaYYWscs0kLWG0v\nVIj1+nxoj+PO0pdzeHHNzeTSl2zQ2aem43wo56WilsHihJPWPiTTkJoQ7ogNFyvBIzi0jk9h\nrKS5NntlXa1Rl1l3En0dP3e0qOHRou+vBWep4e5gkyxkQuBLX/4qFGA5HC59iZ442XQZnNqG\nzj+Fk1k38a9QK41IWufqZd7/PpccaIpalrnBUA2gmKHctDUubpc+GW4Rybasy+V5+gJM21LI\nlW3CzcETQkOs9RjroPm2kecVOtUebVuS5BzHD0kMKemxtmPaoJ6fJTEEWfNsYhPJFXRpB++Y\nDHyy7lr6hi9piYFtpJclJ0qzZ03b7JZmbVus1HDOeuxtgMqP0Tf44Y7lbwWoe2UbelyEz9C6\ndfaKO/HVPmNbWXjME2MFwDc4IvLpZyD8P0kOzvsonMtCAyXSK7Jn4+R+ieHUPuMuDpUdxn71\noVXRxlA6RRRtK77frmxroz0/n2kG/t6cdYWvRTPcFK0qNNpp2NXWD4JGsqcp+5Z1ORPHsDEK\nW41Jws3lK0LD6UTLsWfxEpbqnTyFC/xjj5aQLjlHyiWJgb7DE63HtFXF/kuQ5flsvOxiTtOX\nbhK+8r4wGc6wBPeGApSzxEDH5yOcZ03bJEqzdvGsLGtnrlqPoQZHuf1/tOE+FN3KJbEv0m+a\nlU3Z+SWpOdzBdodFbD/7FH0ZYPP0rbhhiy9KcpB+Wpa1xNNiwx9siKm4DFKTJQaaZ8NuEq2i\njGe/RgP8eC8KeIJoKS92PUd/8Q9woTpxmoGevxzWbzqy45NM0W6Fh427O7WHr770acrJZV2c\ngvUGrn5eu5Z10rGeWYbm+lXYF+sEeKfMIx4099PBwPx6GIEdH4GveeAKLhTl9RSU2f4oxdop\n2PjR++1xshVtawyCMqkk4dtfgmA4jiLcidMSpY26TGGtZ3pW5lFa91f0McCyjpLZOBr44qje\nyt9mJvq/pw0QN08wnBdp6ilOrRrKQkmGt5OcXdbFqdiAvuLKndXXhDgXQFIBWlbxM8iUV7+J\noUMQs+SXwRp1WMGrZ4mAngSkamr2ig2ac5jOzJSxC3sOcFym3ppkk8bX4Zyrf7iTwK44bOAQ\nhpniVkkz7LaPjHOQmtnwLk5WQ9B79+fyZr+IYuhx+PAMb8Oc3q57QuDVZdxf1feiKB4kHt+p\nf7bEyMllXZyKDfh8fq2vplREGMcdseFggZCKACEHMik2MC/KFsmvKCpdtIZd1lo2hwvK1dRs\nFhs03fdhQ8Mdu+f03p6L2NTbgsMBljDfEtAWV3w9hZNAFvqYlBG42EDmvC/pjnUsNuA8Ij4+\n5Orzz26TvQG11SiYE1ej5HsLvFsUBrTnxfG3OY5tNYp07EsSDmVmyMllXQ4LJyYLeuLLo38e\nbRCI9c3OsU02ACygkQ3kv82RtPWwV3p7fY9sICQIB1CacCMu09zGPnGTXmZ5rIb7Sk0AV0Y2\n/AaAk+oGGkYJNAIomGHYgT1kF06VZZVA1kVzEcd1xkuXvgxgZIMB0vJ0OLKB+V73hNwu47i2\nGgXWaXqYji+/WgqCNecox81x7KtRlLV/tgzIFSMbzLD3xFdH96jae7SLKIp1ZIMXAY1sIKwL\nv2hSJkc2sBFalkejCdzDlkET9H015HNnHWcN4crIBvrwPcJaaN5RAuONvhhx2sAJnHj/GXfP\nh4MGCl0lU9jkeOmkDMcjGwxIli754GxkA/3aDffWti76eQjGAsqEZngXFLJUQ+yrUWAH9lJZ\nfl0kUoTwqBtiA3oYXqJ7q7M5nXEXHZmT/cyisG0k2tHv/mADTATN9CbMc0EO4GuAqGKG+R6E\nzZDzTEhknpASsG9pHF/cMwygw4/0Ef5ulz2tvAQcivuB5VgDD5GkS2HqaEkDycfL5CSRnIoN\n2CW9nKR3ueXFcKzjBZBU4JbOAGUyn1hxtkKdGXxxYkEnsmWZLEfncUVs+BjgbG82u99jmgGG\nSfV92XS29CB4Q19E3LDkrYtig/sLZfi2fAhQxVoB7q5fYYjfxHY84FU27XCPSFavExxuiA24\nWDIO/Th3cKPJp7QB7ogNhDnHuCnTYgMJtw1gIBl8hPIn9jh3s0noPlITwBWx4SUIShuE7yZv\nw322cU7H27RZlMGWJfxLf8xWyVPTkQmxgS19KYZTscGInX7Ehim6wudFxnf6okLFLBbB0pd7\nStSUNxRyg88GaxRblboZ10nP7E/t2VZc33ZJbGCjriplXmwoq09v8SIjlk3O/NQe5z7m3c1H\nagK4IDakpzeDG8lzWKTehvv3AH96QhwuALek48U8uVAnknd6Vi4TG4zwJzZ8ZhcLMmLraldo\nHYsrWvrS1yp+eUJsaMVn0EoboC6KDT3p2zjzYkMFbTklk4V1gAm80LSXu4jPRrHhfLUKxaEH\nrha22dBwn6+tbMMRzr6V1SGsqk4k7xJBuUxsMMKf2PC5oGGQcLt2hQ0shry09KVj3C8fKuk2\nHsH1nTONaqJJBmy66QL78QeErqiyG7jkGgzGBUSN0sHJKg0NT25FpifeDF748laQZ/CVaJZF\nS+0K22Qx8dzgINLv4b/av5DuI4KbFtoIr5/5xOp5vJAaLMzHh8A1QU/bW9D/ebLeOmdTDV/H\nhvcRaZwmbPBSYwORvA2TPCw2zBFMNctAL+xFILiIVQ32kTUhcoODSAukzVm+GoUQrokN/QBu\nzbzY0Biq2k/DFhXebotCm2N1fKcmQNbFBjYv9ifyR3CFVGnDfde4tRle52QIb9MsD4sNP/DJ\nR0ZkbKc3vNS9gvefQGzwiTwhNmg4I2uAuig29Ae4PfNiw912V9YZsTPMr3QPHhKtT2NMTYCs\niw3Mid0GmtJZf0tfNuccqkb/grwNozwsNszzTnrVkRH7Fr3hXflatCaIxAZfyBNig4ZrITYM\nAmiSebGhlWAEUwKb7ycYUT4ASss+PFkWG7b28zqwNJcnzicP1vwDSRvuTB7QHP3iaKLiXlMe\nFht+Mflz4UhIBGg6QPdZbUB2iQ2Xvp6MCCxx4pLYcA3xhGxhDEfoJFpyJh2nQAuqZE8LJQh3\ncD+A5ANxG5R7R9ypLUgD0V6gDedNLDZq/DrSAe7b//TfguCBwSmRepS4X+wB0g9cERuuoeVJ\ngMjMJ/Yczk2wWdA3v+BTNkni88bXeRy2zt8Dg/cCU5zjxYwen32eR1sCFN0jVnEQJfeLDatM\nGr9uKSAe8phdYkPRTI6zymtiA635dMq82HDpF1sbJmP7lZL2ASiI9cLxDobUBHAoNuCw01t0\nodBUnm8DvOHZkTbc2WoUmi+7CY3AqIrkYbEh9Zlh1sofvTs1xZOMsktsaCSvmvpEXhMbngPo\nnnmxQYCM2OTSdtcniP0AD4rrX1kWG5h/i0e1HVN50u/LTM+Ob7FB88718y62HoqOPCw2CJAR\nESHfhQAAHYJJREFUe2n/PGG7M7vEhqV9d126fNnPAmoC5DWx4QWA3pkXG8SWcmAfOURxOcS6\nfqb/1ByKDbWQAXo93FieOwtCce/EG99iw/+YZjc7Pd609koeFhtEkJZ0dokNN/AFqQJLnOQ9\nsWE4TnhzGRU9rtrNwGFe8lucFeAcV6trV4YogG5OE3mXd92SKwAtXMxbPoVTIp3hCDj9vCY2\nfAvwtNunqSr58rwBbF7mhXs6Wz90WW2ds4mtrQWGmcDWKXR0HrY81xr6O5g5/PWbg1wvNrh0\nGjGcEilG9tnk2PQT+iQRkCaviQ3k8UJLMi82CE9Dm7M2H0KIOFwFYuHVT4ayDlJnqTkSG1K5\nE5dm2i6WZ9o29mDsfB/gX28c32LDVIAgNkO+pHHZgjwsNghA747Ekl1iQ2i5AT9KbyIZV6Vv\nlRhCBP7V85rYgK8it8WGumyVMRtO4JS/kLvwmbdMssqU2PBjX52OvYF5HK6tvfuwPJ9g82Gn\nQ4hxkIIfsWGm7gj1+/4Gfwb5TmyQWLJLbEha/nLTwi0EngcYyp8gW2pdDJRIuVFsQLgtNjQQ\nr919JTlIH8r2pdPUfIgN9+gTbjNKApTYX8/TjY/l2Zh1M6OgbRzf51tsmA3wkt2kxAYxnA8R\nurx6RDGZ2FCLvgveHRwoka4XNDLpxwYU0ok0xYWzhOvLLMQDqgMvG3VuUpeN6+sAIPVcZMf3\nAK+6kK/rBE6J9EaLsPpPz5PVed5vOJWktesl6HbMa2JDdpzmdoA7hJZSOpGsrlEykTX0OszX\nZsKlTibj/rueOIk3QPBhnB4B5kXnfJ7nJ1zfO4AcKLHBJzQiQYlXpTVdetYtC+nX+Jun7ZY8\nJzZQuC02NAGj7OVB3LFKOpEsS6RnRmzAZVpuwh+pKFuvICQEevDypeWJ6xx+Rwiu1m5cAcO3\n2LDI7nOHKLFBBqdEOhH19C2lH5jgM2igC43lTrGBuC423C1etufEYd1fgHUNwsyIDbjETwhG\n+4z+GHqVSeB8TDMtT/TeNo2QKmAeleRbbFhuqhzqUGKDGM7bSFdjRhUL9hk00IXGrhexobnY\nx/WVy7q/AHjZaWpSseE0Thti0weHA4Tha6W0vj7qxauX0Ef+WL48pPF++BYbVhlddHmgxAYx\nnBLp464lyz76g+/PXaALjV0veNTohccIfU17GJ61E+xtOaY/W04PZwn01QQFXHuPPnRDa/+H\nyz4wsoZB0GDno7wOFwyVv/0VLHBKpDvf2uirS9a+0Nii+QzzonamkCs7hZsrMkPgG3lSGdJo\nlwM2ZDJro9BDuyhrXXQiDc1S1t6sAgWCAWgN8jO62xKK/4EG9AK2ckNyMDyVgitfwOCkhwHe\ndlg4zLBna7YXjnzjO2vX4L4FuHFctfvrqc5PSh222hcayzh+hGFdFP14ZiQIN0fjhIadpyQx\nju+VJrXjksRw6ojEkJGx/ZwkawdOyPK8/6jEcGFbiiRr8duvvIfzYOzWk8f+6z2UE+lxs/Xq\n9vOSHOw7aT+WXtgzcWgW3a0LXZkBnfF2Bdo66ndxBZq7rcaBFKa45w5ICufK9nRJqZHdpySG\n5B2yUju7LV1SOLQhIsnB2UMSgzTPGWTnaYnh9H5Z1uK3XZbkYO85WdbEG6dE+qbokHFDisyR\nBMrcQmPXi9jwEcB/AsuJw5pzLNvKAIGJDdpCwTCarbmVWlDrRsUhE8xFfLeEpei/uwWuWrvK\nFNO32CCGEhvEcEqkeuj9ebGogx6RuYXGrhexYZbYL9wVSuTVnAONnaYmEhu0pethKltm+JDu\njBJ7X3HZI+h6dRHATRCB67WtN8X0LTaIocQGMZwSqQgWRnxRSaDMLTR2vWABwEGJaS3ngM33\nUABIqKERaTku47igh+4FsZfeAGuBflTrQQl0ZpIvHD3mSjglUhPsf/jkTlmoTC00dr2MbEh9\nSew0JoMtXI+wOhcJJGtLeBKtJmWEwKtX8Ru0mh1/QSdShTMDADQndfv8JufHoEY2SOCUSH+X\nuOPhO0oE7mxFjWyQ9p3HHfMs52pZzzOgkQ1TeBIz95JiMHwP/txqPI4co38d+E9zm8T3yAYx\n1MgGMRyrdqdmvjlT2jREBL4+0vUiNkgsKDbs1Z51c9MnILFhHEug6dnd5EZo8zf+5sX6pYdI\n2B07BUeaB/czR1Viw7UWG0bp8BEwcCJdL2KDxIBiwxGAGo3aGZfa9h3HJjb8cfItRpaHryaS\nJlAKZ7UG8c/Z92DEQXRlYl0qQ4kN11pseP75ftBqcMsCb/gIGPhCYwrkFMCT6EjhmUCr5Bom\nQy2+6P1Q4nH7oylCP5uIdBQ1u5tcy7eCFU6rdg98STefS1cPlkKJDT4t8Th5DjuTJmdYLM4S\naw6Aaxjd9uRhanqVc0ajy1ITkU7iKhS2Ce85XQTXodhQAj/PZ0VepXxDiQ0+xYaUIBhD/sAn\n3bjctmOxITmcaX4HU5jPho84Z7Rp7b+biHTmT7Cr7EpsuPZiQ91v6Wa2dEEfKZTY4FNsICOa\n7CX/4JPezlFqFrHhP0YSNsX8wm6ciYfQenf/1ijE57NfwAXK21tSU2LDtR/ZMC+0++juBQXD\n6v1AiQ0+xQYG1pnUylEci9jAXM9xv0BXE8nxkmz3EW7brRGJjW4oc5X0AOYAxQglNuSAz4at\nLz/26o7A0kYoscE/YvFRvzfgWBMu4IIWFJ4X8TDkTSfdS/vXnZmVtqGCfzvAvH4LnVwruAKX\n/NpJocQG/xZ0ywV3iiy+ErsVRnA/98EZuimB7hl6IXhPUiOAyri3WB/yEOB5stNyHYoNvv3a\nyaHEBp9iAz8fPu/Gpa4ciQ2loTfpjjH5KmDMQWSoaXUn1pMU1Fo7lv7K29aHQ4kN115s8O3X\nTg4lNvgWGxDH8IG/1VFqBrGhMNxPcBEwzR0yW42iJOjO7RC7cYWzwgPtIoMOJTbkhM8GX37t\n5FBig3+x4TTSwbRmpgOxIT0IWqVW8MZkq1FUBLYeuY4WOJphNEAPSWpKbLj2YoNvv3ZyKLHB\nP5Lxy2FfDtg3EgGa/Es/R6blJepCQyPV34JgqDgGoL8buVTwCXf82smhxAYHFlr74oKA3zhe\nw0iA6isAhgJ86zX1s7h0PNYd6kw1L0DhLG85XtK5OWtCuOnXTgQlNvgXG9honmBDYTgRG9AD\n0YsA43SfeUxsSNthuf8LK4z9BkDma0OJDTkwjcKBXzsRlNjgX2zg60cYJq/6FRtSftqNKzzX\nhkI7Chc/yQ6Zlr40Ym+xqrIcKLHh2osNTvzaiaDEBv9iA2Edq0bXd/7EhtcgnA9bqENOaF+y\nq7KniJyUFoESG6692MD92klLJDGFHF50UGBQYoMTDKecWO449J8PF9fHojbzH1rhmsApkTJi\n16xZs7y0JNC0IpU/KdelzNd2ixIbnFheoZz4yUkcNCSEeQd1P+EwTqCmHC/p3Jw1IZwS6ZUC\nxcIrwjBJoIqHj8MBcrqe3aLEBgdiAxt8+oOT1FBsiOUcKoaiebTHYlj60gJpeSqxIQfEhnIr\nNw3MmCRT7Sqlk2doLbmu3aLEBidiwwTwqNi+U0OxYT4nUrUb6GaTxyIVG+TlqcSGHBAbwi6k\n30XSZA4i+3bdRciqrk/aLUpscCI24FIsxnqxT7FhNCfSrbhIi/f1LBcbpOWpxIYcEBtu/TTj\nrgNnb5AESv2OftdnzBKUsRIbnOBYE/s6slJoDuvufphuzmVjphQCgVMizS+498PSFXr5DBro\nQmNKbPDgqHlRL59ZG6zpDLjGRKrDOIGacrykc3PWhHBKpDVxqelLZsuq7hyBLjSmxAYPTgAY\n/D37Fhv6ciJNvRyurSTGoMSGvCE2VPQXjgS+0JgSGzw4RYnhJDUUG7pzIv1C6sGNXosSG/KG\n2LCg1b+X0tKkrXDbQmNXfl/BsDBqfypJ2SfcJF4RGnbvk8TYu1ea1Pl0iSH5ksSQSs7JDBf2\nyvK8R5a1fXtSpFnLkBiSLnt3T+BKEg6zxiYh9Xxh5/7HoYmhcPZIs3ZZlrVLSRJDSoK01M7L\nCufybumdlmZt7yVp1pIDzTPNmsyQtEeeNdl9k2dNvHFKpNIF2WtQEsi+0Fj6np0Mf0adTSfp\nZ9TG9+YcOlRwGPgOeh8KxtNfSd8cyvGMq422cUqkkxySQJlbaEyJDR5cBJggttiiLC1CiXRH\nAOfJmy36XJw1IZyP/vaFzC00psQGD5IBPvCT2vF7n2JiQzOAvu9tt5mV2JAnxIbkCT2a9pgo\n7dfK3EJjSmzw4ArAYD+pTQE4Tfac3xZm9sqqQ4kNeUFsOFWl5rBxw2pWOy0LlamFxtTIBg/S\nAO72E2c0rvuXmPYp4MJ8dqiRDXlhZEOfTphsaud+fgLboUY2OEIGgD930IMA0EHns8CWilXI\nZXBGpEp81tk/lX0EDHx9JCU2eBEClfzE6QWwgWScRfV0ekDnyZst+lycNSGcEUlbCOusL+Uh\ncCIpscGLgmBY6UOYWjeAkvv2RfO+WDuU2JAXxAbgD9AFX0QKfKExJTZ4URgK+kmtI2XQrD0L\nAF78SNRMUWJDXhAbYPw0xETlIDLgxJyJDaQ1BHnDpbeqtMcWHJdUfjNxIcA6YWpKbMgLYkMD\nHYElTpTY4BTvA3hfK8dNI+803A3oMnUewJZrmS8Fh3CnQ1YOJTY4s0wE8L7R9wGMsYWOwDlI\nGd8A2D9Wvs+TN1v0uThrQuQkkZTY4MUnAN60twKMtgS+/FBhXKJl38cAR4WpKbEhL4gNmYcS\nG5yJDTMAjnt21pt94SOWszHDNfeMkc2KVWJDXhAbMg8lNjgTG74y+F84uQxggCXwF4xINz7b\nCEDMfyU25AWxIfNQYoMz/OB1bLe5YEHTMkcMYzyu7AJ3G61wDaDEhtyRge1e7yfT2UJ7lpfo\naA+RigV6nrzZos/FWRNCiQ125ITYYPB+Mp7xxZLv55BczFBWnJoSG5TYYI1yPYoNBu8nrzG+\nbDYHxiWUuMdvgTtbhBIblNhgwXUpNpz29sE+wfjyhzkwOrFryAwPiFNTYoMSGxQIOm34mP86\nFML4ssJkPkVJ9OgUZngtB3Kn4BdKbMgdGYgHGMzftf9wTWGRKWgvgKKbZjPDx4GeJ2+26HNx\n1oRQYoMdOSE2JFKKPHh4wAJC/uBEmkdWzfHczPVBAF3JAmb4QpyaEhvyjdggnLepxAZnYsNl\nSpFbhuHsvmhOpDlnQmEhtyUd+IoeeIyk4rqxMFecmhIb8oPYMBNRauZMu0WJDc7EhlRKkboD\noSghSziRZsUCvEENCwYeqR/UgR54gZCP0LBEnJoSG/KD2NC78NPDhxcfPtxuUWKDM6RTioTf\nDsEZi+7kRPp0LQAuk1MBIgEK0APv0KfrqyYQIv8sK+QgXKra/dBsI6kqMiixwaGF97ZCcl1t\nAMPkZVibI6SoPqLhUwz1nMnZkLPz5M0WfS7OmhButZGOdXyrkui4EhuciQ0klNNll77O8th5\nAA8R9IoCBhnvv8myNp8SG/KJ2JD+yUOiw0pscCY2kEKcLh103tQqAtCFPtKesaoHMdQe6e1V\nYkN+EBs4Al1oTIkNBmhVuNpgQCSNrf9+g4VKlGZNiQ35QWzgCHShMQUDSnC+lDUSqRlbOIlj\ndk5nUMEn3CRSoAuNKbHBgFKcL3z1HOAto1tpK0Lj0U2H/CSW31r0uThrQrhEJNtCY6l/rWZY\nEnUojaQeEm6OxAkN2/dJYuzdIU1qxyWJIe6IxJCWse2AJGv79sryvHOPxHCQ1rUlJ9p+RWI4\nccy429r7Ibrh9dcqsB/FL5BN2rHHebi9+2RZ27ddVjjb42VZO3tAYri0PUVSamSXLAcXt8my\ndiA2VZKDnadlWTtzKNA8p5Ed+yWGuJ3Sh5C2YMWGHWdlWRNv3CGSfaGxq7FbGFZGxaWTq3HC\nzeETQsP2w5IYB3ZJk9qWJDGcPCQxpKfHHpNkbc9BWZ537ZcYTlAiSU4UmywxHD9s3P3bS6Qq\nabE1+a+15Dft2FAebvchWdYO7ZAVDiWSJAdn9kkMybGpklIjOw5LDAmxsqwdi02T5GBXnCxr\np/YHmud0sv2IxHByt/QhjE2SGCjHpScSbdwhUuYWGlNigwGHvUSqQRIi+K9o9GPHMJKHUmJD\n/hYbMrfQmIIBl8M9RKpLSHP+62cyRzumFqDI5XCHSJlbaEyJDUZ86iFSA5LRSZfqvgKdUn4S\ny28t+lycNSFcEhsytdCYGtlgxPceIjW6uv0h/usTMlM7toYH2hcvy5oa2ZBPRjZIoEY2OBzZ\noM02QkSkxf7Ih969Qj6m22D6p41bUCMb8v/IhsDXR1JigxHrPUS6k8YpzPXv1Kp0S1tPt2hZ\nUmJD/hYbEIETScGEkTqRmtGd0vxnDG6qAzyV05lT8AP3iBT4QmNKbDBhsU6k5tRSGdjwBjZd\ntgXAML+J5bcWfS7OmhDKZ4MdOSM26HPMAVrT1HBa0j0AP9N/DZd5F6dQYoMSG+xQYoMJf+pE\nak9TewAg8kMAdByUQW7xOGpQYkP+FxvEUGKDU7HBqzZ0pnGGAWz5FmAKQAFC4mP1MEpsyP9i\ngxhKbHCMrTqRHqQ7rwLs/hHgfYDCOZ0vBSdQDiJzTQb26kQaSi1jAQ4uBBgFUNtZYvmtRZ+L\nsyaEEhvsyCGx4ahOpIU0NVqnO7kCoKRnTAOHEhuU2GCHEhtMOKsTaSNNbVf5yAx+4LgxjBIb\nlNhghxIbzIkD3BAOUOYrTxycLlvDFEaJDUpsUPCD9CCoUAegofcITj8XzPFSyIVQYkPuyUAh\nqN4Y4HavpQol0l0OE8tvLfpcnDUhlNhgRw6JDSQcbrkHoKk3tW6USK1MQZTYoMQGO5TYYEYF\naNoe4D5vajiuoZMpiBIblNhghxIbzKgFkU8AtPbG+YES6WFTECU2KLFBwR8aQ49PATp4D8yn\nRBqUc/lRCABKbMg9Gfjhnj/XA9zvtfxKifS8w8TyW4s+F2dNCHeIRCsph+bMFWkHSmxwLjZQ\nbAbo4U1tJZttboQSG/K32BBGosoNGFJ7kd2ixAbnYgNFLEAvb2r7C0DRv0x2JTbkb7EhjNTf\nQZ+MBnaLEhuciw0Uu/jqYnqcO6Gf2a7EhvwtNoSRm+l9TKputyixISDs5+td6tjwvFroMo/A\nHSKVaVxzINnbeqTdosSGgCxHAN72FUeJDbkga0K4pNqdX/872Rgl+OorsSEgsSE+BOb4Sk2J\nDflbbOAIdMU+JTbYMW9Miq/UlNiQv8UGjkBX7FNiQ8BxlNiQv8UGDuOKfWmbNzJERx2/StKO\nq43a5O9Ntq3Yt34tw29RR+mZjgo3aTJD4Bt5UhnSaKkBG/Jb1uQ5yETWXN7k4qwJN9m1Yp+O\nuLn2YzqU2BBwakpsyN9ig3zFvlNRK6T4eMIkEcZNFB6eNGnCOIlh0qQPpHHGy+PIDOPE+aIY\nL7VIE5NbMpU12XVOmigtHHkceYHKL0ea2sRMFIG8PKVZu2YPwYx5AiyWPsxLsnnFvqv75Rg4\nYIwIHV8QHh4zZkh3iWHMmDYjJYZBD8uivBs5WmJ58GlZnJ6DJYa3Il+VWN6L/J/EMqC37DTy\n1O4fKovzXGeZpcOLMstTD0oMoyPflaY2TGIY2UYW5WVpatLyHDOkh8QgzfOYMW1HSAyPPySL\nIr873UYvFmC9/Gk+bn/4AyeSfMU+X2jeNVqEkq8KD0dHD6ovMURHh3wgMTzcRBZlAXwqsdR4\nWhbntn4SQxR8IbH8Ch9KLF3vlZ1GnlqlF2RxRpaTWW54TWZ5spbE8CkskMUp8brEMLaALMpU\nWCixNHxUFmdAA4lhSG1ZlOiw9ySGPrfLoiyBjyWWuk+IjkrriP6RxRX7fEERKeDUFJHyOZEy\nBUWkgFNTRMr/RBIvNOYLikgBp6aIpIhkhyJSwKkpIuV/IolX7PMFRaSAU1NEyv9EChwtHxRe\nQinZrXpCVrjR0aHjJYZHmsqiLILpEkutobI4jR+TGObBVxLLr0GfSCwP3ic7jTy1KsNkcf5X\nXmYJf1NmeVr2UH4Gi2RxSspSG19QFmUaLJZYbusvizPoVonh6TqyKNGFx0oMfSNkUX4NmiKx\n1BsiOirt3vePbCRSzNKYmJgNmzayLd3EbGTbL//2/o4xbld+bz3i2X7+j/h4zLJ5m9h/wXbG\nBklq366UnCVm7grx8ZiYGRtleZux3nZ8I9su/dn7W9tu0rYzNvJcbrRuv1ktPh6z8c+vxcdj\nNtHyFB6P2bTyW0lq62fEsN+C7ZdrYzay3Fm36z43HTHEkqcWtUJylpjffxAfxzzLUpu1VpLa\nih8lZ6ElvUGS2ncrBce3Ssf/+kc2EklB4fqBIpKCggtQRFJQcAGKSAoKLkARSUHBBSgiKSi4\ngKwSKeP9WuXH4fjwur9p29R+lStp48TZ/hthYWEhb/EDMd29WwdJkTI07mVvUoao1lM5SGx5\nw/KfivPlLzFBahkjyleZbUjNmjUthrPE0odXqrPMR9akRWZNzVrAWSo1Fs1wHcKs+bhOYdZI\n75kulBqPZnk6Aik195FVIm1pmHi8yuaj1c/vqJHGt993TT9UhM2z5Pv0R0ZLPr/zzerdPVsn\nSZ1vrNu0pDxRradykNiFqodPlTspypffxASprb4l8Vj4RXnWeAyHiX13X/z2CpfkWZMWmSU1\nawFnqdR4NO91iLPm4zpFWSM/FJ7pI2sOS41Hsz0dAZSa+8gqkRZOJaTvT9N7EVJ/A9/u3EWO\nV2bTvPk+/TF3BA+85M3unq2TpNbXvPnmH4khKU9U66kcJDb7GULOXBHly29igtQ2N7hwsPgF\nedZ4DIeJDZtISKuV8qxJi8ySmrWAs1RqPJr3OsRZ83Gdoqwdu/vpmT6y5rDUeDTb0xFAqbkP\nF9pIWyqfe+NtQrot4FtCnoEpzKDvX26iuyKI7u7dOkjq9wGJ28sdNialR7WeykFi7/S9u94n\nwnw5Scx2lf0LB00wxbZmDWM4TOzL+85sLPS9r6zJi8yYmrWAs1Rqnmjadciy5us6ramld9w4\nfGbWS41Hsz8dAZWay8gykdLeq7mRvP4OzflPfEuP7S93eGpEBNH3PxpLCO77I5IoKTJgjjEp\njGrcx1M5TGx03QMHqmwS5ct/YvbUFjWL2934hI+ssRgOE7s6rFbHtr/4ypqPR8KQmrGAs1xq\nWmLsiI+s+bhOe2qfvEkokbJcat7yMD8dAZSa68gqkVLbP5FAyLS+hDRYx7czVhHSha0Aw/cJ\nuWu7HtonkexJbaQ13iFzjUnpUa2ncpDYh8MJ6f+lKF9+ExOk9uJkQh6dI88aj+EwsUT6Ir1n\nkzxrvh4JY2rWAs5SqfFo3usQZ83HdQpSe6hS1eKlJme51Hg0+9PhvNTcR1aJ9E0v3B6umXyw\nahrfznow/UyZg96j5GQ1j7smn0SyJxUVmXSi1klDUp6o1lM5SGx3/cRjVbaI8uU3MUFqX7S4\ncKTiennWeAyHiUXfeXl9gwx51nw9EsbUrAWcpVLj0bzXIc6aj+sUZo1oVbsslRqPZns6Aig1\n95FVIj0dEhYWFkWm3dKQNpbZ9urgunU1YZgfnTHEE9onkQRJDa9Wf6ExKW9U66n8J0am1qky\nVZwvf4mJsvZchUqTfGRNi+EssYyhFZru9JE1X4+EKTVrAWep1Fg0w3UIs+bjOoVZ04mUtVJj\n0WxPRwCl5j5Uh6yCggtQRFJQcAGKSAoKLkARSUHBBSgiKSi4AEUkBQUXoIikoOACFJEUFFyA\nIpKCggtQRFJQcAGKSAoKLkARSUHBBSgiKSi4AEUkBQUXoIikoOACFJEUFFyAIpKCggtQRFJQ\ncAGKSAoKLkARSUHBBSgiKSi4AEUkBQUXoIikoOACFJEUFFyAIpKCggtQRFJQcAGKSAoKLkAR\nSUHBBSgiKSi4AEUkBQUXoIikoOACFJEUFFyAIpKCggtQRFJQcAGKSAoKLkARSUHBBSgiKSi4\nAEUkBQUXoIikoOACFJEUFFyAIpKCggtQRFJQcAGKSAoKLkARSUHBBSgiKSi4AEUkBQUXoIik\noOACFJEUFFyAIpKCggtQRFJQcAGKSAoKLkARSUHBBSgiKSi4AEUkBQUXoIikoOACFJEUFFzA\n/wMK1RZcIw8/TgAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PerformanceAnalytics::charts.PerformanceSummary(emh::as_returns(stx40))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  |                                                                            \r",
      "  |                                                                      |   0%\r",
      "  |                                                                            \r",
      "  |===                                                                   |   4%\r",
      "  |                                                                            \r",
      "  |=====                                                                 |   8%\r",
      "  |                                                                            \r",
      "  |========                                                              |  12%\r",
      "  |                                                                            \r",
      "  |===========                                                           |  15%\r",
      "  |                                                                            \r",
      "  |=============                                                         |  19%\r",
      "  |                                                                            \r",
      "  |================                                                      |  23%\r",
      "  |                                                                            \r",
      "  |===================                                                   |  27%\r",
      "  |                                                                            \r",
      "  |======================                                                |  31%\r",
      "  |                                                                            \r",
      "  |========================                                              |  35%\r",
      "  |                                                                            \r",
      "  |===========================                                           |  38%\r",
      "  |                                                                            \r",
      "  |==============================                                        |  42%\r",
      "  |                                                                            \r",
      "  |================================                                      |  46%\r",
      "  |                                                                            \r",
      "  |===================================                                   |  50%\r",
      "  |                                                                            \r",
      "  |======================================                                |  54%\r",
      "  |                                                                            \r",
      "  |========================================                              |  58%\r",
      "  |                                                                            \r",
      "  |===========================================                           |  62%\r",
      "  |                                                                            \r",
      "  |==============================================                        |  65%\r",
      "  |                                                                            \r",
      "  |================================================                      |  69%\r",
      "  |                                                                            \r",
      "  |===================================================                   |  73%\r",
      "  |                                                                            \r",
      "  |======================================================                |  77%\r",
      "  |                                                                            \r",
      "  |=========================================================             |  81%\r",
      "  |                                                                            \r",
      "  |===========================================================           |  85%\r",
      "  |                                                                            \r",
      "  |==============================================================        |  88%\r",
      "  |                                                                            \r",
      "  |=================================================================     |  92%\r",
      "  |                                                                            \r",
      "  |===================================================================   |  96%\r",
      "  |                                                                            \r",
      "  |======================================================================| 100%"
     ]
    }
   ],
   "source": [
    "df_stx40 <- emh::is_random(stx40, a = 0.9999,\n",
    "                           freqs1  = seq(1, 20),\n",
    "                           freqs2 = c(\"Mon\", \"Tue\", \"Wed\", \n",
    "                                      \"Thu\", \"Fri\", \"Week\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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lxjHpInExJCq9WQ+o+NL8bUexacbS7ao++OJy7OnUxICK1GQ1phDowvJ5lV2QVH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\nQmCC",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by frequency”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_frequency(df_stx40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6DkzE0fy53YMxdSySXXFFL1RfFu7o1e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\nEvD/AWVwnmVaa0yuAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by test name”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_test_name(df_stx40)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## The SATRIX Financials Index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "stxfin <- Quandl(\"GOOG/JSE_STXFIN\", \n",
    "                 type = \"zoo\")$Close"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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2IbZz/b1V2iBpHZQGaDJaQ/1E0X1SBd3pwUgDsA3tZ+i51dz0HqrjYOyqjZMLJS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RN8ewm3ckDTQJXmCBt35yQDW2hir1oYWycw0580Z7vokLYhzyVCT/c2wS/emOKbS3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",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PerformanceAnalytics::charts.PerformanceSummary(emh::as_returns(stxfin))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  |                                                                            \r",
      "  |                                                                      |   0%\r",
      "  |                                                                            \r",
      "  |===                                                                   |   4%\r",
      "  |                                                                            \r",
      "  |=====                                                                 |   8%\r",
      "  |                                                                            \r",
      "  |========                                                              |  12%\r",
      "  |                                                                            \r",
      "  |===========                                                           |  15%\r",
      "  |                                                                            \r",
      "  |=============                                                         |  19%\r",
      "  |                                                                            \r",
      "  |================                                                      |  23%\r",
      "  |                                                                            \r",
      "  |===================                                                   |  27%\r",
      "  |                                                                            \r",
      "  |======================                                                |  31%\r",
      "  |                                                                            \r",
      "  |========================                                              |  35%\r",
      "  |                                                                            \r",
      "  |===========================                                           |  38%\r",
      "  |                                                                            \r",
      "  |==============================                                        |  42%\r",
      "  |                                                                            \r",
      "  |================================                                      |  46%\r",
      "  |                                                                            \r",
      "  |===================================                                   |  50%\r",
      "  |                                                                            \r",
      "  |======================================                                |  54%\r",
      "  |                                                                            \r",
      "  |========================================                              |  58%\r",
      "  |                                                                            \r",
      "  |===========================================                           |  62%\r",
      "  |                                                                            \r",
      "  |==============================================                        |  65%\r",
      "  |                                                                            \r",
      "  |================================================                      |  69%\r",
      "  |                                                                            \r",
      "  |===================================================                   |  73%\r",
      "  |                                                                            \r",
      "  |======================================================                |  77%\r",
      "  |                                                                            \r",
      "  |=========================================================             |  81%\r",
      "  |                                                                            \r",
      "  |===========================================================           |  85%\r",
      "  |                                                                            \r",
      "  |==============================================================        |  88%\r",
      "  |                                                                            \r",
      "  |=================================================================     |  92%\r",
      "  |                                                                            \r",
      "  |===================================================================   |  96%\r",
      "  |                                                                            \r",
      "  |======================================================================| 100%"
     ]
    }
   ],
   "source": [
    "df_stxfin <- emh::is_random(stxfin, a = 0.9999,\n",
    "                            freqs1  = seq(1, 20),\n",
    "                            freqs2 = c(\"Mon\", \"Tue\", \"Wed\",\n",
    "                                       \"Thu\", \"Fri\", \"Week\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BASIUEAIRESBBASIUEAIRESBBASIUEAIRESBBASIUEAIRESBBASIUEAIRESBBAS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\nBAj4/4JmABUKD64KAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by frequency”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_frequency(df_stxfin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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hBCsh8hCSGkACEJIyQhhGQ/QhJCSAFCEkZIQgjJfoQkhJAChCSMkIQQkv0ISQgh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\nAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by test name”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_test_name(df_stxfin)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## The SATRIX Financials Index Shuffled"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "One problem with the Lo-MacKinlay variance ratio test is that it is parametric. Meaning that there are two possible interpretations when the test fails. \n",
    "\n",
    "Either the market is not random or the variance of security prices is infinite and the distribution of returns is described by a [stable distribution](https://en.wikipedia.org/wiki/Stable_distribution)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "A few people believe that returns are distributed according to a stable distribution. This version of the random walk hypothesis is known as the [_Stable Paretian Hypothesis_](https://web.williams.edu/Mathematics/sjmiller/public_html/341Fa09/handouts/Fama_MandelbroitAndStableParetianHypothesis.pdf) and was first proposed by Benoit Mandelbrot. If true, then most of modern quantitative finance is wrong because the following things are not possible and / or meaningful,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "* Diversification and, by extension, Mean Variance Optimization\n",
    "* Risk metrics based on full or partial moments (Sharpe, Sortino, etc.)\n",
    "* Most derivatives are also being totally mispriced if this is true"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "One counter argument to it being true is that if daily returns have infinite variance then so should every other frequencies' returns because the characteristic exponent of a stable distribution is invariant in the sampling interval ... but here's a simpler test:\n",
    "\n",
    "If the failed Lo-MacKinlay variance ratio tests are due to the distribution of returns and not because there are patterns which cause the variance ratios to deviate from one, then if I shuffle the returns I should get the same result (the market is non-random). \n",
    "\n",
    "Let's try it and see what happens, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in emh::simulate_permutation(logrets = stxfin_logrets, window = 126):\n",
      "“logrets length is not a multiple of the window size discared the last 14 logrets in the series.”"
     ]
    }
   ],
   "source": [
    "stxfin_logrets <- emh::as_logreturns(stxfin)\n",
    "stxfin_sim <- emh::simulate_permutation(logrets = stxfin_logrets, \n",
    "                                        window = 126)\n",
    "stxfin_logrets <- head(stxfin_logrets, length(stxfin_logrets) - 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kxuFd4BwPCuq6mpafpjs9FVceK5o/2VsT11fPG0Wq3QMy4zsljoMDl1/G3MpL78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\na8RicU5Ojl6vJ137Db7IVCrVsWPH7Dp2djGbzewTt23btpy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CfUc8K5swSo5bsgAAIABJREFU2S/TMHJVoOzp+w5fKPqOnn/++cLCwm+/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\nA0RGRjbXw4Y37NRqOMRkahKuQ+86RWBgIMXKSlw8Qcy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Abm7uI488Iuw3a/gYGY7gA+H+/Xdju7S0eKLJLBRqtfrIkSNHO3deBLNiyc6W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\nTkSuQmCC",
      "text/plain": [
       "Plot with title “”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PerformanceAnalytics::charts.PerformanceSummary(merge(exp(stxfin_logrets)-1, \n",
    "                                                      exp(stxfin_sim)-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"TRUE 0.00047281265294371\"\n",
      "[1] \"TRUE 0.000244905060180935\"\n",
      "[1] \"TRUE 1.7181101847927e-07\"\n",
      "[1] \"TRUE 4.5431159026863e-07\"\n",
      "[1] \"TRUE 4.09480614576749e-10\"\n"
     ]
    }
   ],
   "source": [
    "# Just so you believe me, here are the moments:\n",
    "suppressMessages(library(moments))\n",
    "for(i in seq(1, 5)) {\n",
    "    print(paste(moment(stxfin_logrets, i) == \n",
    "                moment(stxfin_sim, i),\n",
    "                moment(stxfin_logrets, i)))\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "  |                                                                            \r",
      "  |                                                                      |   0%\r",
      "  |                                                                            \r",
      "  |===                                                                   |   4%\r",
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      "  |======================                                                |  31%\r",
      "  |                                                                            \r",
      "  |========================                                              |  35%\r",
      "  |                                                                            \r",
      "  |===========================                                           |  38%\r",
      "  |                                                                            \r",
      "  |==============================                                        |  42%\r",
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      "  |================================                                      |  46%\r",
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      "  |                                                                            \r",
      "  |=================================================================     |  92%\r",
      "  |                                                                            \r",
      "  |===================================================================   |  96%\r",
      "  |                                                                            \r",
      "  |======================================================================| 100%"
     ]
    }
   ],
   "source": [
    "df_stxfin_sim <- emh::is_random(emh::as_levels(stxfin_sim), \n",
    "                                a = 0.9999,\n",
    "                                freqs1  = seq(1, 20),\n",
    "                                freqs2 = c(\"Mon\", \"Tue\", \"Wed\", \n",
    "                                           \"Thu\", \"Fri\", \"Week\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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e8OTexlz/iUUakVtHZeh/aFlLxV78g7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\nAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by frequency”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_frequency(df_stxfin_sim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kXfl+S+SGCKfe/VqfdKT7m+/Csg5XVK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\nkAABhAQIICRAwP8HlXjvCAyFqukAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “Percentage of tests with non-random result by test name”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "emh:::.plot_results_test_name(df_stxfin_sim)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# CONCLUSIONS"
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    "## All Models Are Wrong ... But Some Are Useful"
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    "Security market prices cannot be fully described by random walks. There is little evidence to support the Efficient Market or Random Walk Hypotheses so the true story is probably that security prices contain some noise and some signal."
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    "As such, many of our quantitative models are incorrect meaning that assets are mispriced and risk is misunderstood. But let's not \"throw the baby out with the bathwater\". Random walks aren't perfect but they are the best tool we have right now and they do work."
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    "That said, in the long run I think that we, as an industry, need to adopt semi-stochastic models learnt by Machine Learning algorithms. If ML can learn to [write like Shakespeare](https://techcrunch.com/2014/01/26/swift-speare/), I'm sure it can learn how to simulate stock markets better than random walks!"
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    "## Additional Links, Books, and Papers\n",
    "\n",
    "Thank you for listening, I really hope you enjoyed the talk. Keep your eye on the emh package because I am going to be adding a tonne of new randomness tests to it over the following months. For more information about this topic, please check out the following:\n",
    "\n",
    "* [LINK] [e-m-h.org](http://e-m-h.org/) - contains a great [history](http://e-m-h.org/history.html) of EMH and most [pertinent papers](http://e-m-h.org/key.html).\n",
    "* [BOOK] [A Random Walk Down Wall Street](https://www.amazon.com/Random-Walk-Down-Wall-Street/dp/0393330338) - written by Burton G. Malkiel; an early pioneer of EMH\n",
    "* [BOOK] [A Non-Random Walk Down Wall Street](https://www.amazon.com/Non-Random-Walk-Down-Wall-Street/dp/0691092567) written by Andrew Lo and MacKinlay; a collection of papers.\n",
    "* [BOOK] [The Misbehaviour of Markets](https://www.amazon.com/Misbehavior-Markets-Fractal-Financial-Turbulence/dp/0465043577) - written by Benoit Mandelbrot ... like Taleb's work, except better in every way.\n",
    "* [PAPER] [The Behaviour of Stock Market Prices](https://drive.google.com/file/d/0B-Tg2v8FPT_KWm1VaGlDVFN3bU0/view) - Eugene Fama's original paper on RWH!\n",
    "* [PAPER] [Efficient Capital Markets](https://drive.google.com/file/d/0B-Tg2v8FPT_KbXR5SlQ0bGNHTmc/view) - Eugene Fama's original paper on the EMH!\n",
    "* [PAPER] [On the Impossibility of Information Efficient Markets](https://drive.google.com/file/d/0B-Tg2v8FPT_KUkxuWm9TZ0d4UzA/view) - Grossman and Stiglitz utility-based disproof of EMH\n",
    "* [PAPER] [Noise](https://drive.google.com/file/d/0B-Tg2v8FPT_KMjliRjg0clVpWG8/view) - Fisher Black's contribution to the impossibility debate; \"noise traders\"\n",
    "* [LINKS] [TuringFinance.com](http://www.turingfinance.com/) - lots of long-form essays about randomness and machine learning including:\n",
    "    * [Random Walks Down Wall Street, Stochastic Processes in Python](http://www.turingfinance.com/random-walks-down-wall-street-stochastic-processes-in-python/)\n",
    "    * [Hacking The Random Walk Hypothesis with Python](http://www.turingfinance.com/hacking-the-random-walk-hypothesis/)\n",
    "    * [Stock Market Prices Do Not Follow Random Walks](http://www.turingfinance.com/stock-market-prices-do-not-follow-random-walks/)\n",
    "    * [Lossless Compression and Market Efficiency???](http://www.turingfinance.com/lossless-compression-algorithms-and-market-efficiency/)\n",
    "    * [Testing the Random Walk Hypothesis with R, part 1](http://www.turingfinance.com/testing-the-efficient-market-hypothesis-with-r/)"
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