Modelling structural changes in the volatility process
AbstractGARCH-type models have been very successful in describing the volatility dynamics of financial return series for short periods of time. However, for example macroeconomic events may cause the structure of volatility to change and the assumption of stationarity is no longer plausible. In order to deal with this issue, the current paper proposes a conditional volatility model with time varying coefficients based on a multinomial switching mechanism. By giving more weight to either the persistence or shock term in a GARCH model, conditional on their relative ability to forecast a benchmark volatility measure, the switching reinforces the persistent nature of the GARCH model. Estimation of this benchmark volatility targeting or BVTGARCH model for Dow 30 stocks indicates that the switching model is able to outperform a number of relevant GARCH setups, both in- and out-of-sample, also without any informational advantages.
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Bibliographic InfoPaper provided by Luxembourg School of Finance, University of Luxembourg in its series LSF Research Working Paper Series with number 10-05.
Date of creation: 2010
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GARCH; time varying coefficients; multinomial logit;
Other versions of this item:
- Frijns, Bart & Lehnert, Thorsten & Zwinkels, Remco C.J., 2011. "Modeling structural changes in the volatility process," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 522-532, June.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
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