By |Published On: November 8th, 2014|Categories: Research Insights|

The FT has a great piece called the “Risk-Return relationship has been upended.” The premise is that benchmarking distorts markets. The article inspired me to dig up some more academic research on the subject. Some of the papers/abstracts are below:

Asset Prices and Institutional Investors

Abstract:

We consider an economy populated by institutional investors alongside standard retail investors. Institutions care about their performance relative to a certain index. Our framework is tractable, admitting exact closed-form expressions, and produces the following analytical results. We find that institutions tilt their portfolios towards stocks that compose their benchmark index. The resulting price pressure boosts index stocks. By demanding more risky stocks than retail investors, institutions amplify the index stock volatilities and aggregate stock market volatility and give rise to countercyclical Sharpe ratios. Trades by institutions induce excess correlations among stocks that belong to their benchmark, generating an asset-class effect.

Asset Management Contracts and Equilibrium Prices

Abstract:

We study the joint determination of fund managers’ contracts and equilibrium asset prices. Because of agency frictions, investors make managers’ fees more sensitive to performance and benchmark performance against a market index. This makes managers unwilling to deviate from the index and exacerbates price distortions. Because trading against overvaluation exposes managers to greater risk of deviating from the index than trading against undervaluation, agency frictions bias the aggregate market upwards. They can also generate a negative relationship between risk and return because they raise the volatility of overvalued assets. Socially optimal contracts provide steeper performance incentives and cause larger pricing distortions than privately optimal contracts.

Asset pricing implications of benchmarking: a two-factor CAPM

Abstract:

The paper considers the equilibrium effects of an institutional investor whose performance is benchmarked to an index. In a partial equilibrium setting, the objective of the institutional investor is modelled as the maximization of expected utility (an increasing and concave function, in order to accommodate risk aversion) of final wealth minus a benchmark. In equilibrium this optimal strategy gives rise to the two-beta CAPM: together with the market beta a new risk-factor (termed active management risk) is brought into the analysis. This new beta is defined as the normalized (to the benchmark’s variance) covariance between the asset excess return and the excess return of the market over the benchmark index. The empirical test supports the model’s predictions. The cross-section return on the active management risk is positive and significant, especially after 1990, when institutional investors became the representative agent of the market.

About the Author: Wesley Gray, PhD

Wesley Gray, PhD
After serving as a Captain in the United States Marine Corps, Dr. Gray earned an MBA and a PhD in finance from the University of Chicago where he studied under Nobel Prize Winner Eugene Fama. Next, Wes took an academic job in his wife’s hometown of Philadelphia and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management firm dedicated to an impact mission of empowering investors through education. He is a contributor to multiple industry publications and regularly speaks to professional investor groups across the country. Wes has published multiple academic papers and four books, including Embedded (Naval Institute Press, 2009), Quantitative Value (Wiley, 2012), DIY Financial Advisor (Wiley, 2015), and Quantitative Momentum (Wiley, 2016). Dr. Gray currently resides in Palmas Del Mar Puerto Rico with his wife and three children. He recently finished the Leadville 100 ultramarathon race and promises to make better life decisions in the future.

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