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The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades

Dean Fantazzini and Tamara Shangina

MPRA Paper from University Library of Munich, Germany

Abstract: This paper focuses on the forecasting of market risk measures for the Russian RTS index future, and examines whether augmenting a large class of volatility models with implied volatility and Google Trends data improves the quality of the estimated risk measures. We considered a time sample of daily data from 2006 till 2019, which includes several episodes of large-scale turbulence in the Russian future market. We found that the predictive power of several models did not increase if these two variables were added, but actually decreased. The worst results were obtained when these two variables were added jointly and during periods of high volatility, when parameters estimates became very unstable. Moreover, several models augmented with these variables did not reach numerical convergence. Our empirical evidence shows that, in the case of Russian future markets, T-GARCH models with implied volatility and student’s t errors are better choices if robust market risk measures are of concern.

Keywords: Forecasting; Value-at-Risk; Realized Volatility; Google Trends; Implied Volatility; GARCH; ARFIMA; HAR; Realized-GARCH (search for similar items in EconPapers)
JEL-codes: C22 C51 C53 G17 G32 (search for similar items in EconPapers)
Date: 2019
New Economics Papers: this item is included in nep-cis, nep-for, nep-ore and nep-rmg
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Journal Article: The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades (2019) Downloads
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