Volatility Forecasting Using Threshold Heteroskedastic Models of the Intra-day Range

25 Pages Posted: 28 May 2009

See all articles by Cathy W. S. Chen

Cathy W. S. Chen

Feng Chia University - Department of Statistics; Graduate Institute of Statistics & Actuarial Science, Feng Chia University

Richard H. Gerlach

University of Sydney

Edward M.H. Lin

Graduate Institute of Applied Statistics, Feng Chia University

Date Written: May 27, 2009

Abstract

An effective approach for forecasting return volatility via threshold nonlinear heteroskedastic models of the daily asset price range is provided. The return is defined as the difference between the highest and lowest log intra-day asset price. A general model specification is proposed, allowing the intra-day high-low price range to depend nonlinearly on past information, or an exogenous variable such as US market information. The model captures aspects such as sign or size asymmetry and heteroskedasticity, which are commonly observed in financial markets. The focus is on parameter estimation, inference and volatility forecasting in a Bayesian framework. An MCMC sampling scheme is employed for estimation and shown to work well in simulation experiments. Finally, competing range-based and return-based heteroskedastic models are compared via out-of-sample forecast performance. Applied to six international financial market indices, the range-based threshold heteroskedastic models are well supported by the data in terms of finding significant threshold nonlinearity, diagnostic checking and volatility forecast performance under various volatility proxies.

Keywords: size and sign asymmetry, volatility model, conditional autoregressive range (CARR) model, threshold variable, Bayes

JEL Classification: C11, C15, C22, C51, C52

Suggested Citation

Chen, Cathy W. S. and Gerlach, Richard H. and Lin, Edward M.H., Volatility Forecasting Using Threshold Heteroskedastic Models of the Intra-day Range (May 27, 2009). Available at SSRN: https://ssrn.com/abstract=1410616 or http://dx.doi.org/10.2139/ssrn.1410616

Cathy W. S. Chen

Feng Chia University - Department of Statistics ( email )

100 Wen Hwa Road
Taichung, 407
Taiwan
886 4 24517250 ext 4412 (Phone)
886 4 24517092 (Fax)

HOME PAGE: http://myweb.fcu.edu.tw/~chenws/

Graduate Institute of Statistics & Actuarial Science, Feng Chia University

100 Wenhwa Road
Talchung
Taiwan
886 4-24517250 ext 4412 (Phone)
886 4-2517092 (Fax)

HOME PAGE: http://myweb.fcu.edu.tw/~chenws/

Richard H. Gerlach (Contact Author)

University of Sydney ( email )

Room 483, Building H04
University of Sydney
Sydney, NSW 2006
Australia
+ 612 9351 3944 (Phone)
+ 612 9351 6409 (Fax)

HOME PAGE: http://www.econ.usyd.edu.au/staff/richardg

Edward M.H. Lin

Graduate Institute of Applied Statistics, Feng Chia University ( email )

100 Wen Hwa Road
Taichung, 407
Taiwan

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