Aglo Trader

Intro

This is my repo for backtesting algorithmic trading strategies.

Implemented with Backtrader in Python.

Run a backtest

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

Syntax:

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

Arguments:

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

Tools

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.

Current Implemented Strategies

• Buy and Hold (BuyAndHold.py)
• Simple Moving Average Cross-Over (CrossOver.py)
• Leveraged ETF Pairs (LeveragedEtfPair.py)
• Pair Switching (PairSwitching.py)
• Mean reversion (MeanReversion.py)

Notes:

Pair Switching

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

Backtest results:

2003 - 2013

Method	Value	SPY
Total Returns	525.71%	89.86%
Max Drawdown	16.28%	54.83%
CAGR	20.15%	6.63%
Sharpe	1.03988	0.24775
Sortino	1.52483	0.34871

2013 - 2018

Method	Value	SPY
Total Returns	55.83%	100.92%
Max Drawdown	9.76%	12.93%
CAGR	9.29%	14.99%
Sharpe	0.51831	0.95824
Sortino	0.72603	1.35337

2018 - YTD (09/04/2019)

Method	Value	SPY
Total Returns	14.64%	12.29%
Max Drawdown	12.05%	19.15%
CAGR	8.50%	7.19%
Sharpe	0.43412	0.30127
Sortino	0.58252	0.40374

MeanReversion

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

Possible Enhancements:

Quantopian: Enhancing short term mean reversion strategies

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

Backtest results:

2013 - 2018 (60d lookback, 5d rebalance)

Method	Value	SPY
Total Returns	133.90%	96.88%
Max Drawdown	18.10%	13.04%
CAGR	17.54%	14.52%
Sharpe	0.97543	0.93255
Sortino	1.43594	1.32703

2018 - YTD (12/16/2019) (60d lookback, 5d rebalance)

Method	Value	OEF
Total Returns	33.29%	22.65%
Max Drawdown	20.20%	19.41%
CAGR	13.88%	11.03%
Sharpe	0.66737	0.53051
Sortino	0.94469	0.71488