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GARCH Model with Cross-sectional Volatility; GARCHX Models

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  • Steve Satchell
  • Soosung Hwang

Abstract

This study introduces GARCH models with cross-sectional market volatility, which are called GARCHX models. The cross-sectional market volatility is a special case of common heteroscedasticity in asset specific returns, which is suggested by Connor and Linton (2001) as an important component in individual asset volatility. Using UK and US data, we find that daily return volatility can be better specified with GARCHX models, but GARCHX models do not necessarily perform better than conventional GARCH models in forecasting.

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Bibliographic Info

Paper provided by Warwick Business School, Finance Group in its series Working Papers with number wp01-16.

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Date of creation: 2001
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Handle: RePEc:wbs:wpaper:wp01-16

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  1. Nelson, Daniel B & Cao, Charles Q, 1992. "Inequality Constraints in the Univariate GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 229-35, April.
  2. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
  3. MacDonald, John A & Shawky, Hany A, 1995. "On Estimating Stock Market Volatility: An Exploratory Approach," Journal of Financial Research, Southern Finance Association & Southwestern Finance Association, vol. 18(4), pages 449-63, Winter.
  4. Bulkley, George & Tonks, Ian, 1991. "Cross-sectional Volatility on the U.K. Stock Market," The Manchester School of Economic & Social Studies, University of Manchester, vol. 59(0), pages 72-80, Supplemen.
  5. Engle, Robert F. & Ng, Victor K. & Rothschild, Michael, 1990. "Asset pricing with a factor-arch covariance structure : Empirical estimates for treasury bills," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 213-237.
  6. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
  7. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  8. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2000. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," NBER Working Papers 7590, National Bureau of Economic Research, Inc.
  9. Soosung Hwang & Pedro L. Valls Pereira, 2006. "Small sample properties of GARCH estimates and persistence," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 473-494.
  10. Stephen Satchell & Soosung Hwang & Anthony Hall, 1999. "Using Bayesian Variable Selection Methods to Choose Style Factors in Global Stock Return Models," Working Papers wp99-01, Warwick Business School, Finance Group.
  11. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
  12. Harvey, Andrew C & Shephard, Neil, 1996. "Estimation of an Asymmetric Stochastic Volatility Model for Asset Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 429-34, October.
  13. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
  14. Constantinides, George M & Duffie, Darrell, 1996. "Asset Pricing with Heterogeneous Consumers," Journal of Political Economy, University of Chicago Press, vol. 104(2), pages 219-40, April.
  15. Hwang, Soosung & Salmon, Mark, 2004. "Market Stress and Herding," CEPR Discussion Papers 4340, C.E.P.R. Discussion Papers.
  16. Torben Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," NBER Working Papers 6961, National Bureau of Economic Research, Inc.
  17. Anthony D. Hall & S. Hwang & Steve Satchell, 2000. "Using Bayesian Variable Selection Methods to Choose Style Factors in Global Stock Return," Research Paper Series 31, Quantitative Finance Research Centre, University of Technology, Sydney.
  18. Hull, John C & White, Alan D, 1987. " The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
  19. Hwang, Soosung & Satchell, Stephen E., 2000. "Market risk and the concept of fundamental volatility: Measuring volatility across asset and derivative markets and testing for the impact of derivatives markets on financial markets," Journal of Banking & Finance, Elsevier, vol. 24(5), pages 759-785, May.
  20. Soosung Hwang, 2000. "Properties of Cross-sectional Volatility," Working Papers wp00-05, Warwick Business School, Finance Group.
  21. Connor, Gregory & Korajczyk, Robert A. & Linton, Oliver, 2006. "The common and specific components of dynamic volatility," Journal of Econometrics, Elsevier, vol. 132(1), pages 231-255, May.
  22. Hwang, S. & Satchell, S. E., 1998. "Implied Volatility Forecasting: A Comparison of Different Procedures," Accounting and Finance Discussion Papers 98-af38, Faculty of Economics, University of Cambridge.
  23. Harvey, Campbell R. & Siddique, Akhtar, 1999. "Autoregressive Conditional Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(04), pages 465-487, December.
  24. Soosung Hwang & John Knight & Stephen E. Satchell, 2001. "Forecasting Nonlinear Functions of Returns Using LINEX Loss Functions," Annals of Economics and Finance, Society for AEF, vol. 2(1), pages 187-213, May.
  25. Ferson, Wayne E & Harvey, Campbell R, 1991. "The Variation of Economic Risk Premiums," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 385-415, April.
  26. Braun, Phillip A & Nelson, Daniel B & Sunier, Alain M, 1995. " Good News, Bad News, Volatility, and Betas," Journal of Finance, American Finance Association, vol. 50(5), pages 1575-1603, December.
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Cited by:
  1. Pedro L. Valls Pereira, 2004. "How Persistent is Volatility? An Answer with Stochastic Volatility Models with Markov Regime Switching State Equations," Finance Lab Working Papers flwp_59, Finance Lab, Insper Instituto de Ensino e Pesquisa.
  2. Gilles Dufrénot & Valérie Mignon & Anne Peguin-Feissolle, 2011. "The Effects of the Subprime Crisis on the Latin American Financial Markets: An Empirical Assessment," Working Papers halshs-00587460, HAL.
  3. Heejoon Han & Dennis Kristensen, 2012. "Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates," CREATES Research Papers 2012-25, School of Economics and Management, University of Aarhus.
  4. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, School of Economics and Management, University of Aarhus.
  5. Monica Billio & Massimiliano Caporin & Michele Gobbo, 2006. "Flexible Dynamic Conditional Correlation multivariate GARCH models for asset allocation," Applied Financial Economics Letters, Taylor and Francis Journals, vol. 2(2), pages 123-130, March.

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