A Kernel Technique for Forecasting the Variance-Covariance Matrix
AbstractIn this paper we propose a novel methodology for forecasting variance convariance matrices (VCM) using kernel estimates. While the popular Riskmetrics methodology can be seen as a special case of our methodology, the generalisation is significant as it allows the researcher to use a number of variables to determine the kernel weights of past VCM. The complexity of the methodology scales with the number of explanatory variables used and not with the size of the VCM. This, as well as the automatic positive definiteness of the VCM forecasts are major improvements on currently available forecasting methods. An empirical analysis establishes the usefulness of our proposed methodology.
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Bibliographic InfoPaper provided by Economics, The Univeristy of Manchester in its series Centre for Growth and Business Cycle Research Discussion Paper Series with number 151.
Length: 33 pages
Date of creation: 2010
Date of revision:
Other versions of this item:
- Ralf Becker & Adam Clements & Robert O'Neill, 2010. "A Kernel Technique for Forecasting the Variance-Covariance Matrix," NCER Working Paper Series 66, National Centre for Econometric Research.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-11-13 (All new papers)
- NEP-ECM-2010-11-13 (Econometrics)
- NEP-FOR-2010-11-13 (Forecasting)
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- Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
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