Are there any good research papers which predict market direction which are reproducible?

I am looking for research papers which try to predict the market direction for a specific duration and have been successfully reproduced by people outside of the scientific community (so not just peer reviewed). According to jcl from, most papers in this domain are not reproducible (see

Every second week a new paper about trading with machine learning methods is published (a few can be found below). Please take all those publications with a grain of salt. According to some papers, phantastic win rates in the range of 70%, 80%, or even 85% have been achieved. Although win rate is not the only relevant criterion – you can lose even with a high win rate – 85% accuracy in predicting trades is normally equivalent to a profit factor above 5. With such a system the involved scientists should be billionaires meanwhile. Unfortunately I never managed to reproduce those win rates with the described method, and didn’t even come close. So maybe a lot of selection bias went into the results. Or maybe I’m just too stupid.

A commenter adds:

I have tried many machine learning techniques after reading various ‘peer reviewed’ papers. But reproducing their results remains elusive. When I live test with ML I can’t seem to outperform random entry.

An accuracy of 55% would already be more than enough for me. I am especially interested in machine learning classifiers which return a probability.

Any suggestions for such papers?

Submitted October 10, 2018 at 01:28PM by kalabele


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