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

Valeria Lakshina ()
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Valeria Lakshina: National Research University Higher School of Economics

HSE Working papers from 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.

Keywords: GARCH; stochastic volatility; markov switching multifractal; forecast performance. (search for similar items in EconPapers)
JEL-codes: C01 C51 C58 G17 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2014
New Economics Papers: this item is included in nep-cis, nep-ets, nep-for, nep-ore and nep-tra
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Published in WP BRP Series: Financial Economics / FE, October 2014, pages - 23

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Persistent link: https://EconPapers.repec.org/RePEc:hig:wpaper:37/fe/2014

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