Regime Timing
Mar 14, 2024
Dynamic Warp Analysis: A New Approach for Detecting and Timing Bubbles
By Megan Czasonis, Mark Kritzman, and David Turkington We show how our method of relevance-based prediction implements similar logic to a highly complex machine learning model, but relevance is extremely transparent. What is the best way to form predictions from a data sample? This is a big question, but at its core lies a fundamental tension between explaining the past and anticipating the future. Predictions can fail by paying too little attention to the past (underfitting) or by paying too ...
Mar 13, 2023
Stock Vulnerability and Resilience
By Megan Czasonis, Huili Song, and David Turkington We use a statistical method that combines a stock’s attributes in a nonlinear and conditional way in order to predict its relative vulnerability or resilience to market drawdowns. By definition, a stock market crash corresponds to a severe, market-wide drawdown. However, below the surface, there is often considerable dispersion in the performance of individual stocks during these events. In a recent paper, we explore whether a stock’s unique ...
Jul 1, 2019
Crowded Trades: Implications for Sector Rotation and Factor Timing
By William Kinlaw, Mark Kritzman, and David Turkington Published in the Journal of Portfolio Management, July 2019 The authors propose two measures for managing exposure to bubbles. Together these measures have the potential to locate bubbles in sectors and in factors as they begin to emerge and to identify exit points before they fully deflate.
Jan 1, 2014
Correlation Surprise
By William Kinlaw and David Turkington Published in the Journal of Asset Management, January 2014 We extend Kritzman and Li’s study by disentangling the volatility and correlation components of turbulence to derive a measure of correlation surprise. On average, after controlling for volatility, we find that periods characterized by correlation surprise lead to higher risk and lower returns to risk premia than periods characterized by typical correlations.
Jun 30, 2012
Toward Determining Systemic Importance
By William Kinlaw, Mark Kritzman, and David Turkington Published in the Journal of Portfolio Management, Summer 2012 We extend the absorption ratio methodology to determine the systemic importance of a particular entity.
Jun 1, 2011
Principal Components as a Measure of Systemic Risk
By Mark Kritzman, Yuanzhen Li, Sebastien Page, and Roberto Rigobon. Published in the Journal of Portfolio Management, Summer 2011 recipient of the 2012 Bernstein Fabozzi/Jacobs Levy Outstanding Article Award. We introduce a method for inferring systemic risk from asset prices, and show how investors might use the absorption ratio as an early warning signal of market stress.
1. Peter L. Bernstein Award for Best Article in an Institutional Investor Journal in 2013; Bernstein-Fabozzi/Jacobs-Levy Award for Outstanding Article in the Journal of Portfolio Management in 2006, 2009, 2011, 2013 (2), 2014, 2015, 2016, 2021; Graham & Dodd Scroll Award for article in the Financial Analysts Journal in 2002 and 2010. Roger F. Murray First Prize for Research Presented at the Q Group Conference in 2012, 2021, 2023. Harry M. Markowitz Award for Best Paper in the Journal of Investment Management in 2022, 2023. Doriot Award for Best Private Equity Research Paper in 2022.