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?