Do We Need Stochastic Volatility and GARCH? Comparing Squared End-of-Day Returns on FTSE

29 Pages Posted: 26 Nov 2019

See all articles by David E. Allen

David E. Allen

School of Mathematics and Statistics, The University of Sydney; Financial Research Network (FIRN); Department of Finance; School of Business and Law, Edith Cowan University

Michael McAleer

Erasmus University Rotterdam - Erasmus School of Economics, Econometric Institute; Tinbergen Institute; University of Tokyo - Centre for International Research on the Japanese Economy (CIRJE), Faculty of Economics

Date Written: November 7, 2019

Abstract

The paper examines the relative performance of Stochastic Volatility (SV) and GARCH(1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we use the realized volatility (RV) of FTSE sampled at 5-minute intervals, taken from the Oxford Man Realised Library. Both models demonstrate comparable performance and are correlated to a similar extent with the RV estimates, when measured by OLS. However, a crude variant of Corsi's (2009) HAR model, applied to squared demeaned daily returns on FTSE, appears to predict the daily RV of FTSE better than either of the two models. Quantile regressions suggest that all three methods capture tail behaviour similarly and adequately. This leads to the question of whether we need either of the two standard volatility models, if the simple expedient of using lagged squared demeaned daily returns provides a better RV predictor, at least in the context of the sample.

Keywords: Stochastic Volatility, GARCH(1,1), FTSE, RV 5 Min, HAR Model, Demeaned Daily Squared Returns

JEL Classification: C22, G12

Suggested Citation

Allen, David Edmund and McAleer, Michael, Do We Need Stochastic Volatility and GARCH? Comparing Squared End-of-Day Returns on FTSE (November 7, 2019). Available at SSRN: https://ssrn.com/abstract=3486510 or http://dx.doi.org/10.2139/ssrn.3486510

David Edmund Allen (Contact Author)

School of Mathematics and Statistics, The University of Sydney ( email )

School of Mathematics and Statistics F07
University of Sydney
Sydney, New South Wales 2006
Australia

HOME PAGE: http://www.maths.usyd.edu.au

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Department of Finance ( email )

Taiwan
Taiwan

School of Business and Law, Edith Cowan University

100 Joondalup Drive
Joondalup, WA 6027
Australia

HOME PAGE: http://www.dallenwapty.com

Michael McAleer

Erasmus University Rotterdam - Erasmus School of Economics, Econometric Institute ( email )

Rotterdam
Netherlands

Tinbergen Institute

Rotterdam
Netherlands

University of Tokyo - Centre for International Research on the Japanese Economy (CIRJE), Faculty of Economics

Tokyo
Japan

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