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A Volatility Targeting GARCH model with Time-Varying Coefficients

Author

Listed:
  • Thorsten Lehnert

    (Luxembourg School of Finance, University of Luxembourg)

  • Bart Frijns

    (Department of Finance, Auckland University of Technology, New Zealand)

  • Remco Zwinkels

    (Erasmus School of Economics, Erasmus University Rotterdam.)

Abstract

GARCH-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 volatility targeting or VT-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.

Suggested Citation

  • Thorsten Lehnert & Bart Frijns & Remco Zwinkels, 2009. "A Volatility Targeting GARCH model with Time-Varying Coefficients," LSF Research Working Paper Series 09-08, Luxembourg School of Finance, University of Luxembourg.
  • Handle: RePEc:crf:wpaper:09-08
    as

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    References listed on IDEAS

    as
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    More about this item

    Keywords

    GARCH; time varying coefficients; multinomial logit;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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