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Examining the Sources of Excess Return Predictability: Stochastic Volatility or Market Inefficiency?

Kevin Lansing, Stephen LeRoy and Jun Ma ()

No 2018-14, Working Paper Series from Federal Reserve Bank of San Francisco

Abstract: We use a consumption based asset pricing model to show that the predictability of excess returns on risky assets can arise from only two sources: (1) stochastic volatility of fundamental variables, or (2) departures from rational expectations that give rise to predictable investor forecast errors and market inefficiency. While controlling for stochastic volatility, we find that a variable which measures non-fundamental noise in the Treasury yield curve helps to predict 1-month-ahead excess stock returns, but only during sample periods that include the Great Recession. For these sample periods, higher noise predicts lower excess stock returns, implying that a shortage of arbitrage capital in financial markets caused excess returns to drop below the levels justified by fundamentals. The statistical significance of the predictor variables that control for stochastic volatility are also typically sensitive to the sample period. Measures of implied and realized stock return variance cease to be significant when the COVID-influenced data from early 2020 onward is included.

Keywords: Equity premium; Excess Volatility; return predictability; market sentiment; time series momentum; yield curve noise (search for similar items in EconPapers)
JEL-codes: E44 G12 (search for similar items in EconPapers)
Pages: 45 pages
Date: 2022-01-27
New Economics Papers: this item is included in nep-for, nep-mac and nep-ore
Note: The first version of this paper was December 3, 2018. A previous version was published 09/15/2020..
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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DOI: 10.24148/wp2018-14

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