Forecasting Realized Volatility with Linear and Nonlinear Univariate Models

13 Pages Posted: 24 Jan 2011

See all articles by Michael McAleer

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

Marcelo Medeiros

IPEA - Institute for Applied Economic Research; UnB - University of Brasilia

Abstract

Abstract In this paper, we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 futures. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high-frequency intraday returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analysed in this paper.

Keywords: Bagging, Financial econometrics, Neural networks, Nonlinear models, Realized volatility, Volatility forecasting

Suggested Citation

McAleer, Michael and Medeiros, Marcelo, Forecasting Realized Volatility with Linear and Nonlinear Univariate Models. Journal of Economic Surveys, Vol. 25, Issue 1, pp. 6-18, 2011, Available at SSRN: https://ssrn.com/abstract=1745758 or http://dx.doi.org/10.1111/j.1467-6419.2010.00640.x

Michael McAleer (Contact Author)

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

Marcelo Medeiros

IPEA - Institute for Applied Economic Research ( email )

SBS-01, Ed. BNDES
1610
Brasilia, DF 70076-900
Brazil

HOME PAGE: http://www.ipea.gov.br

UnB - University of Brasilia ( email )

Campus Universitário Darcy Ribeiro
Brasilia, Distrito Federal 70910-900
Brazil

HOME PAGE: http://buscatextual.cnpq.br/buscatextual/visualizacv.do?metodo=apresentar&id=K4798836T3

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