Feature engineering and alpha factor research

More than the raw data, feature engineering is often the key to making signal useful for an algorithm. Leveraging decades of research into risk factors that drive returns on theoretical and empirical grounds is a good starting point to prioritize data transformations that are more likely to reflect relevant information.

However, only creative feature engineering will lead to innovative strategies that can compete in the market over time. Even for new alpha factors, a compelling narrative that explains how they work, given established ideas on market dynamics and investor behavior, will provide more confidence to allocate capital.

The risks of false discoveries and overfitting to historical data make it even more necessary to prioritize strategies prior to testing rather than let the data speak. We covered how to deflate the Sharpe ratio in light of the number of experiments. 

..................Content has been hidden....................

You can't read the all page of ebook, please click here login for view all page.
Reset
44.204.125.111