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I have hourly open,high,low,close candles data for a particular asset. I wrote my own algo and some back testing code that replays the data from the past hourly candles to calculate the total return and total standard deviation. So let's say my set contains 30k hourly candles, I can run my code and replay only first 100, 1k etc.

I'm thinking, how do I annualise the returns of this kind of data? Is it feasible at all or the "error" would be too big? The more general question is how to measure performance of a hourly strategy on an annual basis.

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    $\begingroup$ Isn't it simply R_interval ^ (252*7/k) where k is the number of hourly candles in the test run, and R_interval is the performance of the strategy in this interval. 252 trading days, 7 hours per day. $\endgroup$
    – Sergei Rodionov
    Mar 3, 2021 at 4:31
  • $\begingroup$ Why would you want to or care to annualize? $\endgroup$
    – Dave Harris
    Mar 3, 2021 at 5:05
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    $\begingroup$ Equity returns are not scale invariant. You cannot take short term returns and convert them into annual ones in a meaningful manner. $\endgroup$
    – Dave Harris
    Mar 3, 2021 at 5:05
  • $\begingroup$ I'm just thinking, if I don't annualise, then it's hard to grasp intuitively how much the strategy can make... I guess I could also do a 24h rolling window (24h market) and treat that somehow as a day and then go annual from there. Just thinking out loud. $\endgroup$
    – flojdek
    Mar 3, 2021 at 5:15

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