Aglo Trader

Intro

This is my repo for backtesting algorithmic trading strategies.

Implemented with Backtrader in Python.

python -m backtest.run BuyAndHold -t SPY -s 2010

backtest.run <strategy> -t <tickers list> ...

Arg	Flag	Possible Values	Description
strategy		BuyAndHold, CrossOver, etc.	Choose from the list of algorithms in the ./backtest/algos/. The arg value is the filename.
tickers	-t, --tickers	SPY, AAPL, etc.	A list of tickers to use.
universe	-u, --universe	sp500, faang, etc.	Find the list of uniuverses in ./backtest/utils/universe.py
start	-s, --start	2010, 2010-01-01	Starting date of the backtest
end	-e, --end	2022, 2021-12-31	End date for backtest
cash	--cash	100000	Starting cash balance
verbose	-v, --verbose		Show verbose details of all trades
plot	-p, --plot		Show the full plot
plot returns	--plotreturns		Only plot the returns
kwargs	-k, --kwargs		Additional arguments to pass through to the strategy

python -m tools.download_prices -t SPY

Tool	Description
download_info	Download fundamental data
download_prices	Download price history for specified tickers. If no tickers given, defaults to download all tickers in SP500
update_prices	Updates newest price data and appends to the end of the downloaded file (Use this once you've already downloaded data)
plot	Plot price for specified tickers
validate_data	Cleans up and validates price data
stats	Get statistical data of ticker
etc.	You can follow this format and try out the other tools as well. They can all be imported too.

This strategy has been successful for the ETF pairs MDY and TLT.

Backtest results:

This strategy has been successful for the S&P 100 stocks.

Filter out large 1-day news-realted moves
- (Sort by 5d standard-deviation of returns)

Backtest results: