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Forecasting the daily dynamic hedge ratios in emerging European stock futures markets: evidence from GARCH models

Forecasting the daily dynamic hedge ratios in emerging European stock futures markets: evidence from GARCH models
Forecasting the daily dynamic hedge ratios in emerging European stock futures markets: evidence from GARCH models

This paper empirically estimates and forecasts the hedge ratios of three emerging European and one developed stock futures markets by means of seven different versions of GARCH model. The seven GARCH models applied are bivariate GARCH, GARCH-ECM, BEKK GARCH, GARCH-DCC, GARCH-X, GARCH-GJR and GARCH-JUMP. Daily data during January 2000-July 2014 from Greece, Hungary, Poland and the UK are applied. Forecast errors based on these four stock futures portfolio return forecasts (based on forecasted hedge ratios) are employed to evaluate out-of-sample forecasting ability of the seven GARCH models. The comparison is done by means of model confidence set (MCS) and modified Diebold-Mariano tests. Forecasts are conducted over two non-overlapping out-of-sample periods, a two-year period and a one-year period. MCS results indicate that the GARCH model provides the most accurate forecasts in five cases, while each of the GARCH-ECM, GARCH-X and GARCH-GJR models constitutes model confidence set in four cases at a reasonable confidence level. Models selection based on modified Diebold-Mariano tests further corroborate results of the MCS tests. Differences between the portfolio returns also indicate the high forecasting ability of GARCH-BEKK and GARCH-GJR models.

Emerging market, Forecasting, GARCH, Generalised autoregressive conditional heteroscedastic, Hedge ratio, Volatility
1755-3830
67-100
Choudhry, Taufiq
6fc3ceb8-8103-4017-b3b5-2d38efa57728
Hasan, Mohammad
5d0edc25-d9e7-4705-a750-7c570cbe00d6
Zhang, Yuanyuan
5ccfad72-adee-49aa-a708-f9fdcdbab54e
Choudhry, Taufiq
6fc3ceb8-8103-4017-b3b5-2d38efa57728
Hasan, Mohammad
5d0edc25-d9e7-4705-a750-7c570cbe00d6
Zhang, Yuanyuan
5ccfad72-adee-49aa-a708-f9fdcdbab54e

Choudhry, Taufiq, Hasan, Mohammad and Zhang, Yuanyuan (2019) Forecasting the daily dynamic hedge ratios in emerging European stock futures markets: evidence from GARCH models. International Journal of Banking, Accounting and Finance, 10 (1), 67-100. (doi:10.1504/IJBAAF.2019.099316).

Record type: Article

Abstract

This paper empirically estimates and forecasts the hedge ratios of three emerging European and one developed stock futures markets by means of seven different versions of GARCH model. The seven GARCH models applied are bivariate GARCH, GARCH-ECM, BEKK GARCH, GARCH-DCC, GARCH-X, GARCH-GJR and GARCH-JUMP. Daily data during January 2000-July 2014 from Greece, Hungary, Poland and the UK are applied. Forecast errors based on these four stock futures portfolio return forecasts (based on forecasted hedge ratios) are employed to evaluate out-of-sample forecasting ability of the seven GARCH models. The comparison is done by means of model confidence set (MCS) and modified Diebold-Mariano tests. Forecasts are conducted over two non-overlapping out-of-sample periods, a two-year period and a one-year period. MCS results indicate that the GARCH model provides the most accurate forecasts in five cases, while each of the GARCH-ECM, GARCH-X and GARCH-GJR models constitutes model confidence set in four cases at a reasonable confidence level. Models selection based on modified Diebold-Mariano tests further corroborate results of the MCS tests. Differences between the portfolio returns also indicate the high forecasting ability of GARCH-BEKK and GARCH-GJR models.

Text
IJBAF-Hasan-Choudhry-Zhang-Revised - Accepted Manuscript
Restricted to Repository staff only until 16 April 2020.
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More information

Accepted/In Press date: 24 September 2018
e-pub ahead of print date: 16 April 2019
Keywords: Emerging market, Forecasting, GARCH, Generalised autoregressive conditional heteroscedastic, Hedge ratio, Volatility

Identifiers

Local EPrints ID: 431059
URI: http://eprints.soton.ac.uk/id/eprint/431059
ISSN: 1755-3830
PURE UUID: 117780d2-ea2d-4461-b92e-36a59a58451a
ORCID for Taufiq Choudhry: ORCID iD orcid.org/0000-0002-0463-0662

Catalogue record

Date deposited: 22 May 2019 16:30
Last modified: 24 Jul 2019 00:36

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