Do mean reversion and/or trend following strategies work better than buy and hold for stocks?

I was curious to see if trend following and/or mean reversion strategies outperformed buy and hold with the S&P 500. I repurposed some backtesting scripts that I had written for cryptocurrency (https://github.com/hansenrhan/crypto_backtesting_analysis). The analyses were ran assuming 0 trading fees, but did apply a 30% tax each year if the strategy was profitable that year (since a major advantage of buy and hold is no taxes except when selling). The scripts also assume fractional shares as needed (which isn't quite realistic, but is a carryover from cryptocurrency backtesting).

I looked at hourly data from the past two years using the yfinance library (since hourly data further past than that is not readily available). It would be interesting to look at that in the future.

I looked at four strategies: Mean Reversion w/ Shorting, Mean Reversion w/o Shorting, SMA Crossover w/ Shorting and SMA Crossover w/o Shorting. SMA Crossover strategies performed much higher across the board than Mean Reversion strategies, and only SMA Crossover w/ Shorting beat S&P 500 buy and hold in more than 50% of the runs.

The code can be generalized to any other ticket available with yfinance.

comparison_analysis.html: R Markdown Analysis Output
comparison_analysis.Rmd: R Markdown Analysis
mean_reversion_analysis.ipynb: Mean Reversion Backtester Scripts
sma_crossover_analysis.ipynb: Simple Moving Average (SMA) Crossover Scripts
run_output/: Backtesting Results from Random Parameters

Python:

• yfinance
• seaborn
• matplotlib
• pandas
• numpy
• tqdm

R:

• tidyverse
• ggpubr

Once you've analyzed and discovered the most promising parameters using this backtesting repository, you may want to actually implement the strategies in live trading.

I have developed another script for this purpose: the Alpaca SMA Crossover Trader (https://github.com/hansenrhan/alpaca_sma_crossover_trader). This Python script uses the Alpaca API to execute trades based on the Simple Moving Average (SMA) crossover strategy.

With slight modifications to the code, you can substitute in the parameters for the SMA periods that you discovered using this backtesting analysis.

Please be reminded that this script is for illustrative and educational purposes only. It should not be used for making actual investment decisions without understanding and adjusting it to your specific needs and risk tolerance. Please check out the Alpaca SMA Crossover Trader for more information.