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Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models

Dimos S. Kambouroudis, David G. McMillan, Katerina Tsakou Orcid Logo

Journal of Futures Markets, Volume: 36, Issue: 12, Pages: 1127 - 1163

Swansea University Author: Katerina Tsakou Orcid Logo

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DOI (Published version): 10.1002/fut.21783

Abstract

We investigate the information content of implied volatility forecasts for stock index return volatility. Using different autoregressive models, we examine whether implied volatility forecasts contain information for future volatility beyond that in GARCH and realized volatility models. Results show...

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Published in: Journal of Futures Markets
ISSN: 02707314
Published: 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa34904
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spelling 2020-06-22T14:51:36.7649211 v2 34904 2017-08-11 Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models a4f50625221ac95136b3ff39782f2733 0000-0003-1913-858X Katerina Tsakou Katerina Tsakou true false 2017-08-11 BAF We investigate the information content of implied volatility forecasts for stock index return volatility. Using different autoregressive models, we examine whether implied volatility forecasts contain information for future volatility beyond that in GARCH and realized volatility models. Results show implied volatility follows a predictable pattern and confirm the existence of a contemporaneous relationship between implied volatility and index returns. Individually, implied volatility performs worse than alternate forecasts, however, a model that combines an asymmetric GARCH model with implied and realized volatility through (asymmetric) ARMA models is preferred model for forecasting volatility. This evidence is further supported by consideration of value-at-risk. Journal Article Journal of Futures Markets 36 12 1127 1163 02707314 1 12 2016 2016-12-01 10.1002/fut.21783 COLLEGE NANME Accounting and Finance COLLEGE CODE BAF Swansea University 2020-06-22T14:51:36.7649211 2017-08-11T19:02:19.1047934 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Dimos S. Kambouroudis 1 David G. McMillan 2 Katerina Tsakou 0000-0003-1913-858X 3 0034904-26092018164402.pdf paper_jfm.pdf 2018-09-26T16:44:02.3030000 Output 598817 application/pdf Accepted Manuscript true 2018-09-26T00:00:00.0000000 true eng
title Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models
spellingShingle Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models
Katerina Tsakou
title_short Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models
title_full Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models
title_fullStr Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models
title_full_unstemmed Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models
title_sort Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models
author_id_str_mv a4f50625221ac95136b3ff39782f2733
author_id_fullname_str_mv a4f50625221ac95136b3ff39782f2733_***_Katerina Tsakou
author Katerina Tsakou
author2 Dimos S. Kambouroudis
David G. McMillan
Katerina Tsakou
format Journal article
container_title Journal of Futures Markets
container_volume 36
container_issue 12
container_start_page 1127
publishDate 2016
institution Swansea University
issn 02707314
doi_str_mv 10.1002/fut.21783
college_str Faculty of Humanities and Social Sciences
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hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Accounting and Finance{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Accounting and Finance
document_store_str 1
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description We investigate the information content of implied volatility forecasts for stock index return volatility. Using different autoregressive models, we examine whether implied volatility forecasts contain information for future volatility beyond that in GARCH and realized volatility models. Results show implied volatility follows a predictable pattern and confirm the existence of a contemporaneous relationship between implied volatility and index returns. Individually, implied volatility performs worse than alternate forecasts, however, a model that combines an asymmetric GARCH model with implied and realized volatility through (asymmetric) ARMA models is preferred model for forecasting volatility. This evidence is further supported by consideration of value-at-risk.
published_date 2016-12-01T03:43:20Z
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score 11.017797

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