How long did you paper trade / forward test before deploying a systematic options strategy live? Looking for real experiences.
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Building a systematic strategy around option selling on Indian indices (BankNifty/Nifty). The core logic is Greeks-based — it reacts to how options behave relative to spot moves, so backtesting on end-of-day or even 1-minute OHLC data is basically useless for this. The signals depend on tick-level data of both the index and the option chain simultaneously, which means I can only generate meaningful signal history by running the engine live (paper or real) and logging everything myself.
I've been doing this for a while and have a growing dataset, but I'm genuinely unsure about the threshold where I should feel confident enough to deploy real capital.
A few things I'm wondering:
- How many trades / weeks / months of forward data do you consider the minimum before trusting a strategy?
- Does expiry-day behavior need to be separately validated? (Gamma dynamics feel very different from regular days)
- How do you account for the fact that your early logs might have bugs that skewed results, even if you've since fixed them?
- Is there a statistical framework you use — Sharpe threshold, min sample size for signal reliability, etc. — or is it more gut feel after seeing consistent behavior?
Not looking to get rich overnight, just want to be methodical about this. Would love to hear from people who've actually gone through this process with systematic/algo strategies rather than discretionary ones.
Any hard-learned lessons appreciated.