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Forecasting stock market volatility conditional on macroeconomic conditions

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  • Ralf Becker
  • Adam Clements

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Abstract

This paper presents a GARCH type volatility model with a time-varying unconditional volatility which is a function of macroeconomic information. It is an extension of the SPLINE GARCH model proposed by Engle and Rangel (2005). The advantage of the model proposed in this paper is that the macroeconomic information available (and/or forecasts)is used in the parameter estimation process. Based on an application of this model to S&P500 share index returns, it is demonstrated that forecasts of macroeconomic variables can be easily incorporated into volatility forecasts for share index returns. It transpires that the model proposed here can lead to significantly improved volatility forecasts compared to traditional GARCH type volatility models.

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File URL: http://www.ncer.edu.au/papers/documents/WpNo18June07.pdf
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Bibliographic Info

Paper provided by National Centre for Econometric Research in its series NCER Working Paper Series with number 18.

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Length: 33
Date of creation: 14 Jun 2007
Date of revision:
Handle: RePEc:qut:auncer:2007-93

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Related research

Keywords: Volatility; macroeconomic data; forecast; spline; GARCH.;

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  1. 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.
  2. Hamilton, James D & Gang, Lin, 1996. "Stock Market Volatility and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 573-93, Sept.-Oct.
  3. Andrea Beltratti & Claudio Morana, 2004. "Breaks and Persistency: Macroeconomic Causes of Stock Market Volatility," Working Papers 20, SEMEQ Department - Faculty of Economics - University of Eastern Piedmont.
  4. Muller, Ulrich A. & Dacorogna, Michel M. & Dave, Rakhal D. & Olsen, Richard B. & Pictet, Olivier V. & von Weizsacker, Jacob E., 1997. "Volatilities of different time resolutions -- Analyzing the dynamics of market components," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 213-239, June.
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  6. Torben G. Andersen & Tim Bollerslev, 1996. "Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," NBER Working Papers 5752, National Bureau of Economic Research, Inc.
  7. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
  8. Elena Andreou & Eric Ghysels, 2001. "Detecting Multiple Breaks in Financial Market Volatility Dynamics," University of Cyprus Working Papers in Economics 0202, University of Cyprus Department of Economics.
  9. James D. Hamilton & Dong Heon Kim, 2000. "A Re-examination of the Predictability of Economic Activity Using the Yield Spread," NBER Working Papers 7954, National Bureau of Economic Research, Inc.
  10. Robert F. Engle & Jose Gonzalo Rangel, 2005. "The Spline GARCH Model for Unconditional Volatility and its Global Macroeconomic Causes," Working Papers 2005/13, Czech National Bank, Research Department.
  11. Officer, R R, 1973. "The Variability of the Market Factor of the New York Stock Exchange," The Journal of Business, University of Chicago Press, vol. 46(3), pages 434-53, July.
  12. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
  13. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August.
  14. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
  15. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
  16. Dacorogna, Michael M. & Muller, Ulrich A. & Nagler, Robert J. & Olsen, Richard B. & Pictet, Olivier V., 1993. "A geographical model for the daily and weekly seasonal volatility in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 12(4), pages 413-438, August.
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