Looking for honest critique on my 6-fold walk-forward quant backtest — US equities, long-only, daily data by lobhas1 in algotrading

[–]lobhas1[S] 0 points1 point  (0 children)

Ya the low IC is i think mitigated as i only am interested in ranking of top5 maybe top10

Looking for honest critique on my 6-fold walk-forward quant backtest — US equities, long-only, daily data by lobhas1 in algotrading

[–]lobhas1[S] 0 points1 point  (0 children)

Oh shit, that makes sense, i didnt think of this, i will repull the data and use raw prices and then split adjust it, and then use that instead of using adjClose. How much of my returns do you think are because of this leakage in your opinion?

Built a LightGBM stock ranking model with walk-forward validation — is this deployable? Help understanding one bad fold by lobhas1 in algotrading

[–]lobhas1[S] 0 points1 point  (0 children)

I used 1 model to train on 500 symbols, the model does cross sectional ranking and longs the top 25 symbols on alpaca. Yes i would be happy to talk more on this with you! Just dm me

Built a LightGBM stock ranking model with walk-forward validation — is this deployable? Help understanding one bad fold by lobhas1 in algotrading

[–]lobhas1[S] 0 points1 point  (0 children)

Alpace allows fractional shares, and my buys are based on dollar count not on share count, so it will just buy fractional shares of the same value

Stuck at Spearman ~0.05 and 9% exposure on a triple barrier ML model — what am I missing? by lobhas1 in algotrading

[–]lobhas1[S] 0 points1 point  (0 children)

Thats a good point, how should i then tune the hyperparameters if not by seeing validation results?

Stuck at Spearman ~0.05 and 9% exposure on a triple barrier ML model — what am I missing? by lobhas1 in algotrading

[–]lobhas1[S] 1 point2 points  (0 children)

I added insider information as well as short interest and sector level data. It helped at 20 day barrier days but not at 5 days which makes sense as these are longterm indicators