Forecasting Realized Volatility of Russian Stocks using Google Trends and Implied Volatility

Russian Journal of Industrial Economics, 12(1), 79-88, (2019)

20 Pages Posted: 24 May 2019

See all articles by Timofey Bazhenov

Timofey Bazhenov

affiliation not provided to SSRN

Dean Fantazzini

Moscow School of Economics, Moscow State University; National Research University Higher School of Economics

Date Written: April 8, 2019

Abstract

This work proposes to forecast the Realized Volatility (RV) and the Value-at-Risk (VaR) of the most liquid Russian stocks using GARCH, ARFIMA and HAR models, including both the implied volatility computed from options prices and Google Trends data. The in-sample analysis showed that only the implied volatility had a significant effect on the realized volatility across most stocks and estimated models, whereas Google Trends did not have any significant effect. The out-of-sample analysis highlighted that models including the implied volatility improved their forecasting performances, whereas models including internet search activity worsened their performances in several cases. Moreover, simple HAR and ARFIMA models without additional regressors often reported the best forecasts for the daily realized volatility and for the daily Value-at-Risk at the 1 % probability level, thus showing that efficiency gains more than compensate any possible model misspecifications and parameters biases. Our empirical evidence shows that, in the case of Russian stocks, Google Trends does not capture any additional information already included in the implied volatility.

Keywords: forecasting, realized volatility, value-at-risk, implied volatility, google trends, GARCH, ARFIMA, HAR

JEL Classification: C22, C51, C53, G17, G32

Suggested Citation

Bazhenov, Timofey and Fantazzini, Dean, Forecasting Realized Volatility of Russian Stocks using Google Trends and Implied Volatility (April 8, 2019). Russian Journal of Industrial Economics, 12(1), 79-88, (2019) . Available at SSRN: https://ssrn.com/abstract=3369224

Timofey Bazhenov

affiliation not provided to SSRN

Dean Fantazzini (Contact Author)

Moscow School of Economics, Moscow State University ( email )

GSP-2, Leninskie Gory
Moscow, 119992
Russia
+7 495 5105256 (Phone)
+7 495 5105267 (Fax)

HOME PAGE: https://sites.google.com/site/deanfantazzini/

National Research University Higher School of Economics ( email )

Myasnitskaya street, 20
Moscow, Moscow 119017
Russia

HOME PAGE: http://www.hse.ru/org/persons/11532644

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