3 ms·

I'm also building a data driven (mostly NLP) portfolio optimizer, based on expected utility theory! It's a naive model, but it also has statistical bounds on it

I'm also building a data driven (mostly NLP) portfolio optimizer, based on expected utility theory! It's a naive model, but it also has statistical bounds on its efficiency relative to the regret, which is an interesting bonus. Out of curiosity, what kind of model (loss function) are you using?

philippnagel 11y ago
Still very early. Currently I am planning combining quantitative and qualitative data (mainly NLP and sentiment analysis). The main goal is to build a robust system. Therefor I am working on implementing Minimax and Tail-Risk-Hedging as a Spiking Neural Network.