Modeling 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, the time-varying behavior of investors, for example, may cause the structure of volatility to change and the assumption of stationarity is no longer plausible. 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. The estimation of this benchmark volatility targeting or BVT-GARCH 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 InfoArticle provided by Elsevier in its journal Journal of Empirical Finance.
Volume (Year): 18 (2011)
Issue (Month): 3 (June)
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GARCH Time varying coefficients Multinomial logit;
Other versions of this item:
- Thorsten Lehnert & Bart Frijns & Remco C.J. Zwinkels, 2010. "Modelling structural changes in the volatility process," LSF Research Working Paper Series 10-05, Luxembourg School of Finance, University of Luxembourg.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
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