GARCH model with cross-sectional volatility; GARCHX models
Hwang, Soosung and Satchell, S. (Stephen) (2001) GARCH model with cross-sectional volatility; GARCHX models. Working Paper. Warwick Business School, Financial Econometrics Research Centre, Coventry.
WRAP_Hwang_fwp01-16.pdf - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Official URL: http://www2.warwick.ac.uk/fac/soc/wbs/research/wfr...
This study introduces GARCH models with cross-sectional market volatility, which we call GARCHX model. The cross-sectional market volatility is equlvalent to common heteroskedasticity in asset specific returns, which was 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.
|Item Type:||Working or Discussion Paper (Working Paper)|
|Alternative Title:||Generalized autoregressive conditional heteroskedasticity model with cross-sectional volatility; GARCHX models|
|Subjects:||H Social Sciences > HB Economic Theory|
|Divisions:||Faculty of Social Sciences > Warwick Business School > Financial Econometrics Research Centre
Faculty of Social Sciences > Warwick Business School
|Library of Congress Subject Headings (LCSH):||Heteroscedasticity, Analysis of variance, Economic forecasting, Assets (Accounting)|
|Series Name:||Working papers (Warwick Business School. Financial Econometrics Research Centre)|
|Publisher:||Warwick Business School, Financial Econometrics Research Centre|
|Place of Publication:||Coventry|
|Number of Pages:||35|
|Status:||Not Peer Reviewed|
|Access rights to Published version:||Open Access|
|References:||Andersen, T. and T. Bollerslev, 1998, Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts, forthcoming in International Economic Review. Andersen, T., T. Bollerslev, F. Diebold, P. Labys, 1999, The Distribution of Exchange Rate Volatility, Working Paper FIN-99-059, Department of Finance, Stern School of Business, New York University. Bond, S. A., 1999, Time Varying Skewness and Downside Risk Measurement: A Comparison of Models, Unpublished Manuscript, Faculty of Economics and Politics, Cambridge University. Braun, P A., D. B. Nelson, and A. M. Sunier, 1995, Good News, Bad News, Volatility, and Betas, Journal of Finance 50(5), 1575-1603. Bulkley, G. and I. Tonks, 1991, Cross-sectional Volatility on the U.K. Stock Market, Manchester School of Economics and Social Studies 59(0), Supplement, 72-80. Campbell, J., M. Lettau, B. Malkiel, and Y. Xu, 2001, Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk, Journal of Finance 56(1), 1-43. Connor, G. and O.. Linton, 2001, The Common and Specific Components of Dynamic Volatility, Mimeo, London School of Economics and Political Science. Engle, R. F., 1982, Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of the United Kingdom Inflation, Econometrica 50(4), 987-1007. Engle, R. F., V. K. Ng, and M. Rothchild, 1990, Asset Pricing with a FACTORARCH Covariance Structure: Empirical Estimates for Treasury Bills, Journal of Econometrics 45, 213-237. Ferson, W. E. and C. R. Harvey, 1991, The Variation of Economic Risk Premiums, Journal of Political Economy 99(2), 385-415. Ferson, W. E. and C. R. Harvey, 1991, Sources of Predictability in portfolio returns, Financial Analysts Journal 47, 49-56. Glosten, L. R., R. Jagannathan, and D. E. Runkle, 1993, On the Relation between the Expected Value and the Volatility of the Nomial Excess Return on Stocks, Journal of Finance 48(5), 1779-1801. Hansen, B. E., 1994, Autoregressive Conditional Density Estimation, International Economic Review 35, 705-730. Harvey, C. R. and A. Siddique, 1999, Autoregressive Conditional Skewness, Journal of Financial and Quantitative Analysis 34(4), 465-488 Harvey, A. C., E. Ruiz and N. Shephard, 1994, Multivariate Stochastic Variance Models, Review of Economic Studies 61, 247-264. Harvey, A. C. and N. Shephard, 1993, Estimation and Testing of Stochastic Variance Models, Econometrics discussion paper EM/93/268, London School of Economics. Harvey, A. C. and N. Shephard, 1996, Estimation of an Asymmetric Stochastic Volatility Model for Asset Returns, Journal of Business and Economic Statistics 14, 4, 429-34. Hull, J. C., and A. White, 1987, The Pricing of Options on Assets with Stochastic Volatilities, Journal of Finance 42(2), 281-300. Hwang, S., 2001a, Properties of Cross-sectional Volatility, Financial Econometric Research Centre working paper WP00-4, City University Business School. Hwang, S. and Pedro Valls, 2001b, Properties of Volatility Persistence”, Department of Banking and Finance Working Paper, City University Business School. Hwang, S. and S. E. Satchell, 1998, Implied Volatility Forecasting: A Comparison of Different Procedures Including Fractionally Integrated Models with Applications to UK Equity Options, in J. Knight and S. Satchell eds., Forecasting Volatility in the Financial Markets, Butterworth-Heinemann, London. Hwang, S. and S. E. Satchell, 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 and Finance, forthcoming. Knight, J., S. Hwang, and S. E. Satchell, 2001, Forecasting Nonlinear Functions of Returns Using LINEX Loss Functions, Annals of Economics and Finance, Vol. 2, 187-213. Jones, C. 2001, Extracting Factors from Heteroskedastic Asset Returns, forthcoming in Journal of Financial Economics. MacDonald, J. A. and H. Shawky, 1995, On Estimation Stock Market Volatility: An Exploratory Approach, Journal of Financial Research 18(4), 449-463. Apegis, N. T., 1998, Stock Market Volatility and Deviations from Macroeconomic Fundamentals: Evidence from GARCH and GARCH-X Models, Kredit und Kapital, Heft 3, 400-412. Taylor, S. J., 1986, Modeling Financial Time Series, Chichester.|
Actions (login required)