A Stock Return Decomposition Using Observables
77 Pages Posted: 20 Mar 2022 Last revised: 29 Dec 2022
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A Stock Return Decomposition Using Observables
Date Written: March 4, 2022
Abstract
We propose a method to decompose realized stock returns period by period. First, we argue that one can directly estimate expected stock returns from securities available in modern financial markets (using the real yield curve and the Martin (2017) equity risk premium). Second, we derive a new decomposition of realized returns into components due to changes in real yields, equity risk premia, expected dividends, and the realized dividend yield. The stock price elasticities with respect to these inputs are determined by dividend strip weights which can be estimated from dividend futures prices. We apply our method to decompose quarterly and annual realized S&P500 returns going back to 2004Q4. Change to real yields generate a large positive return component in periods of crisis and a large negative return component during periods of monetary tightening, while we find a substantial negative return component from higher equity risk premia in crisis periods. Adding to the growing literature on the stock market during COVID, we furthermore provide a detailed decomposition of the realized stock return for 2020. Risk premium changes drove much of the crash and rebound in the S&P500 in 2020 while a fall in long-term real yields drove a strong positive return for 2020 as a whole.
JEL Classification: G10, G12, G14
Suggested Citation: Suggested Citation