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Volatility Forecast in Crises and Expansions

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  • Sergii Pypko

    () (Department of Economics, University of Western Ontario, Social Science Centre Rm 4064, London, N6A5C2, Canada)

Abstract

We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of threshold-autoregressive models, where changes in regimes are governed by past returns. The ability to capture changes in volatility regimes and using more accurate volatility measures allow outperforming other benchmark models, such as linear heterogeneous autoregressive model and GARCH specifications. Finally, we show how to derive closed-form expression for multiple-step-ahead forecasting by exploiting information about the conditional distribution of returns.

Suggested Citation

  • Sergii Pypko, 2015. "Volatility Forecast in Crises and Expansions," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 8(3), pages 1-26, August.
  • Handle: RePEc:gam:jjrfmx:v:8:y:2015:i:3:p:311-336:d:53754
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    References listed on IDEAS

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    Keywords

    volatility forecast; non-linear time series models;

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • E - Macroeconomics and Monetary Economics
    • F2 - International Economics - - International Factor Movements and International Business
    • F3 - International Economics - - International Finance
    • G - Financial Economics

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