Practical Applications of Identifying Economic Regimes: Reducing Downside Risks for University Endowments and Foundations

Abstract

Overview

Institutional investors, particularly nonprofits who rely on their endowments, must protect their capital from worst-case scenarios of major financial crashes, situations that frequently involve contagion—increases in correlation and volatility.

In Identifying Economic Regimes: Reducing Downside Risks for University Endowments and Foundations , authors John Mulvey and Han Liu of Princeton University develop a machine-learning algorithm to identify financial regimes and help investors more accurately model downside risk.

They find that a multiregime simulation provides more accurate estimates, and they also demonstrate the advantages of adjustable-spending rules during drawdown periods

“In the two-regime approach, you get fatter tails, and the worst-case distributions tend to be more historically accurate than using data from a single regime,” explains Mulvey.