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How to generate AI Alpha Factor in Python
Machine Learning to combine multiple alpha factors for quant trading
I described basics of alpha research in my previous post — How to Build Quant Algorithmic Trading Model in Python and backtesting process in How to Perform Backtesting in Python. Here’s how to apply machine learning technique in generating a better alpha from a number of alpha factors. There are many different ways to achieve this and what I applied here is a classification by supervised machine learning, taking a quantised one-week forward return as the label and calculate the weighted sum of probability of each label.
Features
In Section 3 of the previous post, I used the following three factors (zscore of the rank) and simply took the average to calculate the final alpha signal.
- Momentum 1 Year Factor
- Mean Reversion 5 Day Sector Neutral Smoothed Factor
- Overnight Sentiment Smoothed Factor
Now, taking these as a part of features for machine learning, let’s consider some more features.
