I have a strategy that I've been playing with and trying to backtest. It's of questionable practicality at the moment, but the idea is to pick one stock from the Dow 30 companies to trade right near the close and sell the following day, also near the close (I'm using actual closes as a proxy). If there are no suitable options, no trade is made for the day.
Here's a summary of the test trades:
Period: 6/2/2016 to 6/9/2020 Trading days: 1013 Number of trades: 734 Average return per trade: 0.2298% Trade standard deviation: 2.2826%
From what I've seen, the Sharpe Ratio would typically be calculated something like this in Python:
sharpe = daily_mean_return / daily_std * 252**0.5
In my case, I'm wondering if I should use the average number of days per year rather than
252 for a full year. So it would look something like:
trading_days = 1013 n_trades = 734 trade_mean = 0.002298 trade_std = 0.022826 annual_trades = n_trades / (trading_days / 252) sharpe = trade_mean / trade_std * annual_trades**0.5 # 1.360 daily_sharpe = trade_mean / trade_std * 252**0.5 # 1.598
So calculating using only the trades actually made yields
1.360 and calculating based on
252 days yields
1.598. Which of these is really getting to the essence of the ratio?