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I used it in live trading last year, I couldn't really make it work.

I precalc my stoplosses + stopgains then use a simulation to get the win/loss probabilities on training data.

What I observed is the kelly formula really prefers the tiny stoplosses, so when you sort your predictions by kelly score it will pick the ones with tiny stoplosses.

What happened to me in the live test is the tiny stoplosses triggered, when a stopgain would have triggered later.

I know someone is going to say "thats a problem with your stoplosses+stopgains OOS performance" and they are right, but OOS stoploss+stopgain calculation isn't trivial for me to calculate :\



Where did you get the distribution of the real data from?


Yes, model predictions on volume+price data from 2019+2020




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