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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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Paper provided by Warwick Business School, Financial Econometrics Research Centre 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. Constantinides,George & Duffie,Darrel, 1992. "Asset pricing with heterogeneous consumers," Discussion Paper Serie A 381, University of Bonn, Germany.
   
   • 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.
2. John Y. Campbell, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, 02.
   
   • Malkiel, Burton & Campbell, John & Lettau, Martin & Xu, Yexiao, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Scholarly Articles 3128707, Harvard University Department of Economics.
   • 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.
3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-059, New York University, Leonard N. Stern School of Business-.
   
   • 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.
   • Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
4. Soosung Hwang, 2000. "Properties of Cross-sectional Volatility," Working Papers wp00-05, Warwick Business School, Financial Econometrics Research Centre.
5. 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.
6. Hwang, Soosung & Salmon, Mark, 2004. "Market stress and herding," Journal of Empirical Finance, Elsevier, vol. 11(4), pages 585-616, September.
   
   • Hwang, Soosung & Salmon, Mark, 2004. "Market Stress and Herding," CEPR Discussion Papers 4340, C.E.P.R. Discussion Papers.
7. 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.
8. Soosung Hwang & Pedro L. Valls Pereira, 2006. "Small sample properties of GARCH estimates and persistence," European Journal of Finance, Taylor and Francis Journals, vol. 12(6-7), pages 473-494.
   
   • Hwang. S. & Pedro L. Valls Pereira, 2003. "Small Sample Properties of GARCH Estimates and Persistence," Finance Lab Working Papers flwp_48, Finance Lab, Insper Instituto de Ensino e Pesquisa.
9. Hall, Anthony D. & Hwang, Soosung & Satchell, Stephen E., 2002. "Using Bayesian variable selection methods to choose style factors in global stock return models," Journal of Banking & Finance, Elsevier, vol. 26(12), pages 2301-2325.
   
   • Anthony Hall & Soosung Hwang & Stephen E. Satchell, 2000. "Using Bayesian Variable Selection Methods to Choose Style Factors in Global Stock Return Models," Econometric Society World Congress 2000 Contributed Papers 1213, Econometric Society.
   • 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, Financial Econometrics Research Centre.
10. 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.
    
    • Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
11. 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.
    
    • Robert F. Engle & Victor Ng & Michael Rothschild, 1988. "Asset Pricing with a Factor Arch Covariance Structure: Empirical Estimates for Treasury Bills," NBER Technical Working Papers 0065, National Bureau of Economic Research, Inc.
12. 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.
13. 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.
14. 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.
15. 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.
16. 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.

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Citations

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Cited by:

1. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, School of Economics and Management, University of Aarhus.
2. 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.
3. Gilles Dufrénot & Valérie Mignon & Anne Péguin-Feissolle, 2010. "The Effects of the Subprime Crisis on the Latin American Financial Markets: an Empirical Assessment," Working Papers 2010-11, CEPII research center.
   
   • Dufrénot, Gilles & Mignon, Valérie & Péguin-Feissolle, Anne, 2011. "The effects of the subprime crisis on the Latin American financial markets: An empirical assessment," Economic Modelling, Elsevier, vol. 28(5), pages 2342-2357, September.
   • 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.
4. 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.
5. Soosung Hwang & Steve E. Satchell & Pedro L. Valls Pereira, 2004. "How Persistent is Volatility? An Answer with Stochastic Volatility Models with Markov Regime Switching State Equations," Econometric Society 2004 Latin American Meetings 198, Econometric Society.
   
   • 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.
6. Md. Arifur Rahman, 2007. "The Information Content of Cross-sectional Volatility for Future Market Volatility: Evidence from Australian Equity Returns," Frontiers in Finance and Economics, SKEMA Business School, vol. 4(1), pages 91-124, June.

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