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Stock return predictability and variance risk premia: statistical inference and international evidence

  • Tim Bollerslev
  • James Marrone
  • Lai Xu
  • Hao Zhou

Recent empirical evidence suggests that the variance risk premium, or the difference between risk-neutral and statistical expectations of the future return variation, predicts aggregate stock market returns, with the predictability especially strong at the 2-4 month horizons. We provide extensive Monte Carlo simulation evidence that statistical finite sample biases in the overlapping return regressions underlying these findings can not ``explain" this apparent predictability. Further corroborating the existing empirical evidence, we show that the patterns in the predictability across different return horizons estimated from country specific regressions for France, Germany, Japan, Switzerland and the U.K. are remarkably similar to the pattern previously documented for the U.S. Defining a "global" variance risk premium, we uncover even stronger predictability and almost identical cross-country patterns through the use of panel regressions that effectively restrict the compensation for world-wide variance risk to be the same across countries. Our findings are broadly consistent with the implications from a stylized two-country general equilibrium model explicitly incorporating the effects of world-wide time-varying economic uncertainty.

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Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2011-52.

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Date of creation: 2011
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Handle: RePEc:fip:fedgfe:2011-52
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  1. Tim Bollerslev & Natalia Sizova & George Tauchen, 2009. "Volatility in Equilibrium: Asymmetries and Dynamic Dependencies," CREATES Research Papers 2009-05, School of Economics and Management, University of Aarhus.
  2. Jonah B. Gelbach & Doug Miller, 2009. "Robust Inference with Multi-way Clustering," Working Papers 99, University of California, Davis, Department of Economics.
  3. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2011. "Robust Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 238-249, April.
  4. Geert Bekaert & Eric Engstrom & Yuhang Xing, 2006. "Risk, Uncertainty and Asset Prices," NBER Working Papers 12248, National Bureau of Economic Research, Inc.
  5. Geert Bekaert & Robert J. Hodrick, 1991. "Characterizing Predictable Components in Excess Returns on Equity and Foreign Exchange Markets," NBER Working Papers 3790, National Bureau of Economic Research, Inc.
  6. Erik Hjalmarsson, 2008. "Predicting global stock returns," International Finance Discussion Papers 933, Board of Governors of the Federal Reserve System (U.S.).
  7. John Y. Campbell, 1993. "Why Long Horizons: A Study of Power Against Persistent Alternatives," NBER Technical Working Papers 0142, National Bureau of Economic Research, Inc.
  8. Andrew Ang & Geert Bekaert, 2001. "Stock Return Predictability: Is it There?," NBER Working Papers 8207, National Bureau of Economic Research, Inc.
  9. Xavier Gabaix, 2008. "Variable Rare Disasters: An Exactly Solved Framework for Ten Puzzles in Macro-Finance," NBER Working Papers 13724, National Bureau of Economic Research, Inc.
  10. Philippe Mueller & Andrea Vedolin & Hao Zhou, 2011. "Short Run Bond Risk Premia," FMG Discussion Papers dp686, Financial Markets Group.
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