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The Shape of the Risk Premium: Evidence from a Semiparametric Generalized Autoregressive Conditional Heteroscedasticity Model

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  • Linton, Oliver
  • Perron, Benoit

Abstract

We examine the relationship between the risk premium on the Center for Research on Security Prices (CRSP) value-weighted index total return and its conditional variance. We propose a new semiparametric model in which the conditional variance process is parametric and the conditional mean is an arbitrary function of the conditional variance. For monthly CRSP value-weighted excess returns, the relationship between the two moments that we uncover is nonlinear and nonmonotonic.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 21 (2003)
Issue (Month): 3 (July)
Pages: 354-67

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Handle: RePEc:bes:jnlbes:v:21:y:2003:i:3:p:354-67

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Cited by:
  1. Linton, Oliver & Sancetta, Alessio, 2009. "Consistent estimation of a general nonparametric regression function in time series," Journal of Econometrics, Elsevier, vol. 152(1), pages 70-78, September.
  2. Christian Conrad & Enno Mammen, 2008. "Nonparametric Regression on Latent Covariates with an Application to Semiparametric GARCH-in-Mean Models," Working Papers 0473, University of Heidelberg, Department of Economics, revised Jul 2008.
  3. Bent Jesper Christensen & Morten ├śrregaard Nielsen & Jie Zhu, 2007. "Long Memory in Stock Market Volatility and the Volatility-in-Mean Effect: The FIEGARCH-M Model," CREATES Research Papers 2007-10, School of Economics and Management, University of Aarhus.
  4. Jie Zhu, 2008. "FIEGARCH-M and and International Crises: A Cross-Country Analysis," CREATES Research Papers 2008-16, School of Economics and Management, University of Aarhus.
  5. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.

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