Out of curiosity, how long does this take to run a backtest?
I store adjusted prices, and at the beginning of the backtest I precompute and cache some stats, like all moving averages, all breakouts, risk etc. Then backtest just feeds in the current caapital and current price. For 12 instruments and 20 years this takes about 25 min, on a modern CPU. Granted, it's in Python and I haven't bothered to optimize so it only runs on a single core.
The full backtest with all 37 instruments that I trade in paper account with all historical data that I have (1990 or later, depending on the instrument) takes hours, like many hours but less than a day
don't remember exactly, maybe 3-4h?. It's not optimised for it, as in reality, a lot of heavy operations would be done only once a day and then cached for the rest of the day, but when I run it in the backtest mode on EOD prices it recomputes everything on every tick (in this mode I only substitute one module of the system that normally feeds RT bid-ask ticks from IB to instead read EOD prices from a database add and subtract average bib-ask spread for this contract making 2 prices Bid and Ask out of a single EOD price).
The purpose of this is also to test my system in the exact conditions as if it was running in reality and see what comes out.
I have good hardware (btw, noways one can buy a used double-xeon-CPU+256GBRam+Chinese-brand motherboard with 2 sockets online for like 1000$, which is a beast of a machine, so hardware is definitely cheaper than my time and sanity to endlessly optimise all of that
). The biggest reason for slowness is that I also run it in a single thread, but I can't really make it parallel, I don't know how to split it. Per instrument wouldn't work because there are some tnter-instrument-dependencies and I can't run different time intervals in parallel either because there's still some path-dependence in the system(e.g. when we calculate the current overall portfolio risk for the risk-overlay, or the current drawdown to reduce the current base-capital, etc., although some of these things can probably be ignored in a backtest..)
But again, what I'm doing isn't really a backtest, it's just sort of technical quality-control\test of the system. A real research-style backtest is probably more appropriate to do in a vectorized form in some "matrix calculator" like matlab\python\R, ignoring certain not too-important things to make it possible and fast..
Btw, all the P&L stats I calculate on the individual contracts, because that's what I actually bought and sold in reality. And for things like volatility I use Rob's formulas (btw, the excel spreadsheets from here
https://www.systematicmoney.org/systematic-trading-resources were quite useful for implementation as I remember )
