Beta is time-varying. There is no dispute about this. The traditional approach to addressing this problem is to utilize a rolling window to adjust beta over time; however, this method does not account for the changing environment. It just increases the use of new information.
A new paper, "Conditional Betas: A Non-Standard Approach," attempts to find a new method to account for changing beta. It compares the quality of beta forecasts with one of the leading alternatives of windsorizing the data for beta. The overall effect of a simple machine learning approach is very positive. Results are strong and only based on past price data. This is worth further exploration.
I cannot tell you how frustrating it is to see a hedge balanced trade fall apart because the beta estimate is wrong. Market neutral is no longer market neutral. This may not seem like a significant issue for long-only managers, but for a long/short portfolio, it is a substantial problem.
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