The Scale of Predictability
Federico M. Bandi
University of Chicago - Booth School of Business
University of Montreal - Department of Economics; Center for Interuniversity Research and Analysis on Organization (CIRANO); University of Montreal - Center for Interuniversity Research in Econometrics
London School of Economics & Political Science (LSE)
Bocconi University, IGIER and CAREFIN
August 13, 2015
Stock return predictive relations found to be elusive when using raw data may hold true for different layers in the cascade of economic shocks. Consistent with this logic, we model stock market returns and their predictors as aggregates of uncorrelated components operating over different scales and introduce a notion of scale-specific predictability, i.e., predictability on the components. We formalize the theoretical link between predictability on the components and long-run predictability for the raw series. Empirically, we provide remarkably strong evidence of compensations for variance risk in stock market returns - as well as of an unusually clear link between macroeconomic uncertainty (as captured by consumption variance) and uncertainty in financial markets - at frequencies lower than the business cycle. The existence of low-frequency compensations for variance risk is justified in the context of a component-wise asset pricing model with Epstein-Zin recursive preferences.
Number of Pages in PDF File: 60
Keywords: long run, predictability, aggregation, risk-return trade-off, Fisher hypothesis
JEL Classification: C51, E32, G12, G17
Date posted: December 5, 2012 ; Last revised: August 14, 2015
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