Dead Alphas as Risk Factors
Journal of Asset Management 19(2) (2018) 110-115, Invited Editorial
9 Pages Posted: 1 Aug 2017 Last revised: 26 Feb 2018
Date Written: July 31, 2017
We give an explicit algorithm and source code for extracting equity risk factors from dead (a.k.a. "flatlined" or "hockey-stick") alphas and using them to improve performance characteristics of good (tradable) alphas. In a nutshell, we use dead alphas to extract directions in the space of stock returns along which there is no money to be made (and/or those bets are too volatile). In practice the number of dead alphas can be large compared with the number of underlying stocks and care is required in identifying the aforesaid directions.
Keywords: Expected Return, Stock, Equities, Market, Alpha, Optimization, Trading, Quant, Weights, Asset Allocation, Portfolio, Risk Model, Risk Factor, Specific Risk, Regression, Factor Model, Principal Components, Volatility, Correlation, Covariance, Sharpe Ratio, Position Data, Machine Learning, Source Code
JEL Classification: G00
Suggested Citation: Suggested Citation