Working on a side project and want to sanity-check demand before I sink more time into it.
The problem: free data (Yahoo Finance, most APIs) only gives you today's S&P 500 constituents projected backward, so any backtest quietly excludes every company that got delisted, went bankrupt, or was acquired. This inflates backtested returns — some studies put it at 1.5-2%/year. The fix exists (Norgate, CRSP) but it's priced for professionals — Norgate's cheapest survivorship-bias-free tier runs $630/year, CRSP is priced for institutions/universities.
What I'm considering building: a cheaper, narrower alternative — just S&P 500 point-in-time membership + delisting-adjusted returns (using the standard academic imputed-return convention, not necessarily full delisted OHLC ticks), sold as a simple CSV/API subscription at a lower price point than the existing options.
Questions for anyone doing retail systematic/quant work:
- Do you currently deal with this problem, and how are you handling it (paying for Norgate, ignoring it, building your own scraper)?
- Would a cheaper, narrower version (S&P 500 only, to start) be useful to you, or is broader coverage (Russell, international, futures) a dealbreaker from day one?
- Roughly what would you expect to pay for something like this?
Not selling anything yet — genuinely trying to figure out if this is worth building or if everyone already has this solved. Appreciate any honest feedback, including "this already exists and you should use X instead."
Riley George
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