A tool that helps manage the directional risk of your portfolio.
The purpose of this code is to take your portfolio of stocks, normalize the portfolios price changes to a whole market etf and control directional risk.
The delta value's of your stocks and options can be added up to get a whole portfolio delta. Then all you need to do is look at your reference etf and estimate how your own portfolio is going to move.
If you have positive delta and the market is going up, then you can add to your positions. Positive delta in a bear market, then you can sell call options or add to your short / negative delta positions.
The idea is all you need to get a handle of your portfolio is to look at one stock, the whole market etf. Usually people default to SPY, but this tool will even help you choose your best reference etf.
- Beta Weighted Delta of Options and Underlyings
- Correlation Matrix of Portfolio to Reference Stocks
The project is currently using yfincane to download its stock data. To use the code first download each python file and use the function as you see fit. The first thing to do is to write the ticker symble of the stocks you want to use in the stocks.txt file.
An example of its use is given in main.py which you can run in python.
What to import
from StockCorrMatrix import StockCorrelationMatrix
from BetaWeightedDelts import BetaWeightedDelta
from GrabStockData import grabDataInputs And Outputs
StockCorrelationMatrix(dir, plot = True)
Input :
dir -> directory of all stock data
plot -> if you want to see a heat map of the correlation matrix
Output :
corr_sorted : Correlation Matrix
highest_corr : Stocks with the higher number of correlation to
other stocks in the folder. This can be used as the reference stock.
BetaWeightedOption(beta, StockPrice, ReferencePrice, OptionDelta)
To calculate the beta weighted delta on an option.
Input:
beta : beta of underlying
StockPrice : Current Price of underlying
ReferencePrice : Current Price of the stock you beta weighted the
portfolio to
OptionDelta : The Delta value of the option you want to trade
(belonging to the underlying you
provided.)
Output:
beta : beta of option weighted to the reference stock.
BetaWeightedDelta(StockName, ReferenceName, plot = True)
Find the beta of a underlying using historic price data. You can
download price data off of yahoo finance.
Inputs :
StockName = Directory to you Stock (use the stock ticker as file
name)
ReferenceName = Directory to you Stock (use the stock ticker as
file name)
Use yahoo finance histric prices and place them all in the same
folder.
The number of data points can be different, the function will
adjust the sizes.
plot : If you want to see a plot of the percent price changes and
the beta regression line you also get the R^2 value for a wellness
of fit.
Output :
Beta : beta weighting of your stocks delta
R^2 : wellness of fit of the beta
grabData(linesToSkip = 1)
Input :
linesToSkip : by default the first line of stocks.txt is tickers. The code is asked to skip this line. If it does not it will treat the phrase tickers as a symble.
Output :
Saves a file called data.csv in the correlation folder. The file includes everything you requested to download.
On How To Code Yourself:
[1] Kevin Mooney (2020) How to Calculate Beta-Weighted Delta. Available
at: [YouTube](https://www.youtube.com/watch?v=YLxV5L6IaFA) (Accessed: 23
August 2020).
[2] Kevin Mooney (2020) Calculating the Correlations Between Stocks Using
Python. Available at:
[YouTube](https://www.youtube.com/watch?v=Oa7br3Okxac&t=190s)
(Accessed: 23 August 2020).
On How To Manage A Core Portfolio and Use Beta Weighted Delta:
[3] T. (2016). Small Accounts: The Core Portfolio (1 of 6). Retrieved
August 23, 2020, from
[tastytrade.com](https://bit.ly/2Et98eA)
- LinkedIn - @sina sartipzadeh