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SpxStrategyGraph.py
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SpxStrategyGraph.py
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# PyAlgoSamples
# Examples using the PyAlgoTrade Library
#
# Copyright 2015-2017 Isaac de la Pena
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
.. moduleauthor:: Isaac de la Pena <isaacdlp@agoraeafi.com>
"""
from pyalgotrade import strategy, plotter
from pyalgotrade.barfeed import yahoofeed
from pyalgotrade.technical import ma
from pyalgotrade.stratanalyzer import drawdown, returns, sharpe, trades
from pyalgotrade.utils import stats
from pyalgoext import volatility
class MyStrategy(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, smaShort, smaLong):
strategy.BacktestingStrategy.__init__(self, feed, 10000)
self.__position = None
self.__instrument = instrument
# We'll use adjusted close values instead of regular close values.
self.setUseAdjustedValues(True)
self.__smaShort = ma.SMA(feed[instrument].getPriceDataSeries(), smaShort)
self.__smaLong = ma.SMA(feed[instrument].getPriceDataSeries(), smaLong)
self.getBroker().getFillStrategy().setVolumeLimit(None)
def getSMAShort(self):
return self.__smaShort
def getSMALong(self):
return self.__smaLong
def onEnterOk(self, position):
execInfo = position.getEntryOrder().getExecutionInfo()
self.info("BUY %i shares at $%.2f Portfolio $%.2f" % (execInfo.getQuantity(), execInfo.getPrice(), self.getBroker().getEquity()))
def onEnterCanceled(self, position):
self.__position = None
def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
self.info("SELL %i shares at $%.2f Portfolio $%.2f" % (execInfo.getQuantity(), execInfo.getPrice(), self.getBroker().getEquity()))
self.__position = None
def onExitCanceled(self, position):
# If the exit was canceled, re-submit it.
self.__position.exitMarket()
def onBars(self, bars):
# Wait for enough bars to be available to calculate a SMA.
if self.__smaLong[-1] is None:
return
bar = bars[self.__instrument]
# If a position was not opened, check if we should enter a long position.
if self.__position is None:
if self.__smaShort[-1] > self.__smaLong[-1]:
# Enter a buy market order for as many shares as we can. The order is good till canceled.
amount = int(0.95 * self.getBroker().getEquity() / bar.getAdjClose())
self.__position = self.enterLong(self.__instrument, amount, True)
# Check if we have to exit the position.
elif self.__smaShort[-1] < self.__smaLong[-1] and not self.__position.exitActive():
self.__position.exitMarket()
def run_strategy(index, startYear, endYear, smaShort, smaLong):
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
feed.sanitizeBars(True)
for year in range(startYear, endYear):
feed.addBarsFromCSV(index, "./data/" + index + "-" + str(year) + ".csv")
# Evaluate the strategy with the feed.
myStrategy = MyStrategy(feed, index, smaShort, smaLong)
# Attach analyzers to the strategy.
# Returns first in case others use it (DataSeries)
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
returnsAnalyzer.getReturns().setMaxLen(300000)
sharpeAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
myStrategy.attachAnalyzer(drawDownAnalyzer)
tradesAnalyzer = trades.Trades()
myStrategy.attachAnalyzer(tradesAnalyzer)
volaAnalyzer = volatility.VolaAnalyzer(120)
myStrategy.attachAnalyzer(volaAnalyzer)
# Attach a plotter to the strategy
plt = plotter.StrategyPlotter(myStrategy)
plt.getInstrumentSubplot(index).addDataSeries("SMA Short", myStrategy.getSMAShort())
plt.getInstrumentSubplot(index).addDataSeries("SMA Long", myStrategy.getSMALong())
volaSeries = volaAnalyzer.getVolaSeries()
plt.getOrCreateSubplot("Volatility").addDataSeries("Volatility", volaSeries)
# Run the strategy
myStrategy.run()
# Show basic information
myStrategy.info("Valor final de la cartera: $%.2f" % myStrategy.getBroker().getEquity())
myStrategy.info("Ratio de Sharpe Anualizado: " + str(sharpeAnalyzer.getSharpeRatio(0.0036, True)))
myStrategy.info("DrawDown Maximo: " + str(drawDownAnalyzer.getMaxDrawDown()))
myStrategy.info("DrawDown Mas Largo: " + str(drawDownAnalyzer.getLongestDrawDownDuration()))
meanProfit = stats.mean(tradesAnalyzer.getProfits())
myStrategy.info("Ganancia Media: " + str(meanProfit))
meanLoss = stats.mean(tradesAnalyzer.getLosses())
myStrategy.info("Perdida Media: " + str(meanLoss))
myStrategy.info("Num Ops Igual: " + str(tradesAnalyzer.getEvenCount()))
myStrategy.info("Num Ops Gano: " + str(tradesAnalyzer.getProfitableCount()))
myStrategy.info("Num Ops Pierdo: " + str(tradesAnalyzer.getUnprofitableCount()))
allRet = returnsAnalyzer.getReturns()
#print len(allRet)
myStrategy.info("Rent Media: " + str(stats.mean(allRet)))
posRet = []
negRet = []
allRet = returnsAnalyzer.getReturns()
for ret in allRet:
if ret > 0:
posRet.append(ret)
elif ret < 0:
negRet.append(ret)
myStrategy.info("Ganancia Media: " + str(stats.mean(posRet)))
myStrategy.info("Perdida Media: " + str(stats.mean(negRet)))
myStrategy.info("Vola Media: " + str(stats.mean(volaSeries[-60:])))
# Plot the strategy.
plt.plot()
run_strategy("^GSPC", 2010, 2016, 50, 200)