I’ve read over briefly both this article and the previous one in the series. Thank you for putting these together!
What I’m curious about in quant trading is the actual implementation. Once you, say, have a model which you think works, how important is latency? How do you make decisions about when to buy / sell? (Partially echoing Romeo’s sentiment about curiosity around stop losses and the actual nitty-gritty of extracting value after you think you’ve figured something out.)
In this case the latency is not a big issue because you’re trading on day bars. So if it takes you a few minutes to get into the position, that seems fine. (But that’s something you’d want to measure and track.)
In these strategies you’d be holding a position every bar (long or short). So at the end of the day, once the day bar closes, you’d compute your signal for the next day and then enter that position. If you’re going to do stop-losses that’s something you’d want to backtest before implementing.
Overall, you’ll want to start trading some amount of capital (may be 0, which is called paper trading) using any new strategy and track its performance relative to your backtest results + live results. A discrepancy with backtest results might suggest overfit (most likely) or market conditions changing. Discrepancy with live results might be a result of order latency, slippage, or other factors you haven’t accounted for.
I’ve read over briefly both this article and the previous one in the series. Thank you for putting these together!
What I’m curious about in quant trading is the actual implementation. Once you, say, have a model which you think works, how important is latency? How do you make decisions about when to buy / sell? (Partially echoing Romeo’s sentiment about curiosity around stop losses and the actual nitty-gritty of extracting value after you think you’ve figured something out.)
In this case the latency is not a big issue because you’re trading on day bars. So if it takes you a few minutes to get into the position, that seems fine. (But that’s something you’d want to measure and track.)
In these strategies you’d be holding a position every bar (long or short). So at the end of the day, once the day bar closes, you’d compute your signal for the next day and then enter that position. If you’re going to do stop-losses that’s something you’d want to backtest before implementing.
Overall, you’ll want to start trading some amount of capital (may be 0, which is called paper trading) using any new strategy and track its performance relative to your backtest results + live results. A discrepancy with backtest results might suggest overfit (most likely) or market conditions changing. Discrepancy with live results might be a result of order latency, slippage, or other factors you haven’t accounted for.
I see. Thanks for providing the additional info!