Forecasting Volatility under Fractality, Regime-Switching, Long Memory and Student-t Innovations
AbstractWe examine the performance of volatility models that incorporate features such as long (short) memory, regime-switching and multifractality along with two competing distributional assumptions of the error component, i.e. Normal vs Student-t. Our precise contribution is twofold. First, we introduce a new model to the family of Markov-Switching Multifractal models of asset returns (MSM), namely, the Markov-Switching Multifractal model of asset returns with Student-t innovations (MSM-t). Second, we perform a comprehensive panel forecasting analysis of the MSM models as well as other competing volatility models of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) legacy. Our cross-sections consist of all-share equity indices, bond indices and real estate security indices at the country level. Furthermore, we investigate complementarities between models via combined forecasts. We find that: (i) Maximum Likelihood (ML) and Generalized Method of Moments (GMM) estimation are both suitable for MSM-t models, (ii) empirical panel forecasts of MSM-t models show an improvement over the alternative volatility models in terms of mean absolute forecast errors and that (iii) forecast combinations obtained from the different MSM and (FI)GARCH models considered appear to provide some improvement upon forecasts from single models
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Bibliographic InfoPaper provided by Kiel Institute for the World Economy in its series Kiel Working Papers with number 1532.
Length: 35 pages
Date of creation: Jul 2009
Date of revision:
Multiplicative volatility models; long memory; Student-t innovations; international volatility forecasting;
Other versions of this item:
- Lux, Thomas & Morales-Arias, Leonardo, 2010. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2676-2692, November.
- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-07-28 (All new papers)
- NEP-CBA-2009-07-28 (Central Banking)
- NEP-ECM-2009-07-28 (Econometrics)
- NEP-ETS-2009-07-28 (Econometric Time Series)
- NEP-FOR-2009-07-28 (Forecasting)
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