Language
English (en)
Date of Award
Spring 5-15-2023
Degree Type
Dissertation
Degree Name
Doctor of Business Administration (DBA)
Chair and Committee
Guofu Zhou
Committee Members
Brett Green, Andreas Neuhierl,
Abstract
In an attempt to explain stock prices in a simple and articulate manner, researchers in asset pricing have long employed a “one model fits all prices over time” approach. In this thesis, a regime-switching linear asset pricing model, conditioned on trailing market volatility, is introduced in an attempt to map specific linear model specifications to specific macroeconomicconditions which are quantifiable and observable at t. Called the Time-Robust Iterative Adaptive LASSO (TRIAL) model, this model computes the expected return more efficiently out-of-sample than a benchmark model which does not use volatility-defined regimes, yielding a risk-adjusted mean monthly return of 1.36%, compared to the “no regime” model return of 1.12%. Compared to a seminal model in asset pricing, the Fama-French 3-Factor Model (“FF3”), the TRIAL model evinces a higher monthly return than the FF3’s return of 1.23%, while also providing lower monthly volatility than the FF3, at 6.31% and 6.97%, respectively. The TRIAL model fits its distinct regimes well, having statistically significant, unique linear specifications for each regime. The TRIAL model is asymmetric to the popular size and value factors across the regimes: it estimates big firms better than small firms and value firms better than growth firms. When four single-sort out-of-sample portfolios are created on size and value, the “big firm” portfolio yields a risk-adjusted mean monthly return of 2.38% and a Sharpe ratio of 1.27 over the 17-year testing period, well above any other benchmark model in the study.
Recommended Citation
Baines, David, "The Efficacy of a Regime-Switching Asset Pricing Model Conditioned on Market Volatility" (2023). Olin Business School Electronic Theses and Dissertations. 13.
https://openscholarship.wustl.edu/olin_etds/13