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A Skewed GARCH-in-Mean Model: An Application to U.S. Stock Returns

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  • Pentti Saikkonen
  • Markku Lanne

Abstract

In this paper we consider a GARCH-in-Mean (GARCH-M) model based on the so-called z distribution. This distribution is capable of modeling moderate skewness and kurtosis typically encountered in financial return series, and the need to allow for skewness can be readily tested. We apply the new GARCH-M model to study the relationship between risk and return in monthly postwar U.S. stock market data. Our results indicate the presence of conditional skewness in U.S. stock returns, and, in contrast to the previous literature, we show that a positive and significant relationship between return and risk can be uncovered, once an appropriate probability distribution is employed to allow for conditional skewness

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Bibliographic Info

Paper provided by Econometric Society in its series Econometric Society 2004 North American Summer Meetings with number 469.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:nasm04:469

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Keywords: Conditional skewness; GARCH-in-Mean; Risk-return tradeoff;

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  1. Christoffersen, Peter & Heston, Steve & Jacobs, Kris, 2006. "Option valuation with conditional skewness," Journal of Econometrics, Elsevier, Elsevier, vol. 131(1-2), pages 253-284.
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Cited by:
  1. Matteo Pelagatti, 2007. "Modelling good and bad volatility," Working Papers, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica 20071101, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
  2. Riccardo Borgoni & Piero Quatto & Giorgio Somà & Daniela de Bartolo, 2007. "A Geostatistical Approach to Define Guidelines for Radon Prone Area Identification," Working Papers, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica 20071102, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.

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