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Practical Keras
The problem
Numerai is a hedge fund that gives you an obfuscated financial dataset which you use to predict new unseen market data and if you are correct you can then earn some money in the form of NMR* in essence a fund that crowdsourced most of its quant division.
I wrote a now slightly dated article a few years ago, but is still relevant if you want more background.
And straight from the horse’s mouth 🐴 :
* It is unfortunately not as straightforward as predict right and make money, you need to first buy NMR (a cryptocurrency ) with your own money and then stake it on your predictions, if your predictions are wrong you lose money if they are correct you earn a percentage on your stake.You can read more about payouts here: Staking and PayoutsWhile we are here I should also mention that “practical" is a relative term, some people are curing disease with AI while we are predicting the stock market so for some it might not seem practical. I mean practical here in the sense that this is a current, real problem with consequences (you can make/lose money) as opposed to an imagined or academic one like predicting house prices in the 80’s.
The actual problem
Historically some statistical models have fared better in the competition; XGboost for instance is what Numerai itself uses as an example and it ranks top 50 consistently, but as they themselves mention having a single type of model does not help diversify their meta model so I wanted to try Keras and this is the result which hopefully also serves as a Keras/Numerai beginners tutorial/crash course. Let’s start with an overview of the datasets you are given:
