Forecasting Volatility of Turkish Markets: A Comparison of Thin and Thick Models
Volatility of financial markets is an important topic for academics, policy makers and market participants. In this study first I summarized several specifications for the conditional variance and also define some methods for combination of these specifications. Then assuming that the squared returns are the benchmark estimate for actual volatility of the day, I compare all of the models with respect to how much efficient they are to mimic the realized volatility. At the same time I used a VaR approach to compare these forecasts. With the help of these analyses I examine if combination of the forecast could outperform the single models.
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- Stock, James H. & Watson, Mark W., 1999.
Journal of Monetary Economics,
Elsevier, vol. 44(2), pages 293-335, October.
- James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
- Diebold, Francis X, 1988. "Serial Correlation and the Combination of Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(1), pages 105-111, January.
- Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
- Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Peter Pauly, 1986. "Structural change and the combination of forecasts," Special Studies Papers 201, Board of Governors of the Federal Reserve System (U.S.). Full references (including those not matched with items on IDEAS)
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