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The Fluke Of Stochastic Volatility Versus Garch Inevitability : Which Model Creates Better Forecasts?

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  • Valeria V. Lakshina

    (National Research University Higher School of Economics)

Abstract

The paper proposes the thorough investigation of the in-sample and out-of-sample performance of four GARCH and two stochastic volatility models, which were estimated based on Russian financial data. The data includes Aeroflot and Gazprom’s stock prices, and the rouble against the US dollar exchange rates. In our analysis, we use the probability integral transform for the in-sample comparison, and a Mincer-Zarnowitz regression, along with classical forecast performance measures, for the out-of-sample comparison. Studying both the explanatory and the forecasting power of the models analyzed, we came to the conclusion that stochastic volatility models perform equally or in some cases better than GARCH models.

Suggested Citation

  • Valeria V. Lakshina, 2014. "The Fluke Of Stochastic Volatility Versus Garch Inevitability : Which Model Creates Better Forecasts?," HSE Working papers WP BRP 37/FE/2014, National Research University Higher School of Economics.
    • Handle: RePEc:hig:wpaper:37/fe/2014
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    More about this item

    Keywords

    GARCH; stochastic volatility; markov switching multifractal; forecast performance.;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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