Understanding Security Sensitivity to Good and Bad Times Through Mixture Models
We explore how to leverage Gaussian Mixture Models (GMM) to model regime dependent betas.
While investors have often suspected that a security’s price sensitivity to the overall market varies across time, and can change dramatically during periods of market turmoil, it’s not entirely clear how to measure this phenomenon.
One approach taken is to divide up our historical sample of security prices, and subjectively judge which periods we believe represent the regimes of interest (e.g. periods of low vs high market volatility, periods of market drawdowns, etc).
While this approach can be useful, its main drawback is how it relies on our subjective assessments of what represented historically a “good” or “bad” period for the market.
In this article, we’ll instead turn to an alternative approach that relies on statistically modelling the processes underlying the security in question (and the market as a whole) as Gaussian mixtures.
