For all the quant traders out there, how do you combine signals? What are the pitfalls, hard learnt lessons? @therobotjames @macrocephalopod @HangukQuant @macro_srsv @robertmartin88
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Replying to @skajbaje @therobotjames and
1/ Agree with the other answers. If your forecasts are on a fixed-ish horizon and you have a lot of data on the performance of your forecasts, MVO or some kind of Kelly scheme would probably do quite well (check out Ernie Chan's Quantitative Trading book)
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Replying to @robertmartin88 @skajbaje and
2/ If you have forecasts with different horizons, the "proper" way to do it is multi period opt. Classic reference is Boyd et al's Multi Period Trading via Convex Optimisation (see their package cvxportfolio). But in practice this is quite tricky.
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Replying to @robertmartin88 @skajbaje and
3/ A heuristic is to multiply your older forecasts by some decay factor then just do single period opt. E.g if one of your signals was from a week ago, you multiply it by some e^(-kt) to get it's one day ahead forecast.
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Replying to @robertmartin88 @skajbaje and
4/4 Also I think it's worth checking out the literature on aggregrating probability estimates. In superforecasting tetlock mentions that you shouldn't just take the average – you should subsequently extremise this average else you lose information. e.g Satopaa and Ungar 2015)
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Basically agree with all the above. Point 4/4 needs care. If you are forecasting a real-valued qty like a return, then extremisation happens naturally in any reasonable regression framework. You don’t need to extremist further after getting your regression coefs.
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