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Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models

Chuxuan Xiao Orcid Logo, Winifred Huang Orcid Logo, David P. Newton

Review of Quantitative Finance and Accounting, Volume: 63, Pages: 979 - 1006

Swansea University Author: Chuxuan Xiao Orcid Logo

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DOI (Published version): 10.1007/s11156-024-01279-z

Abstract

We investigate the performances of the ARFIMA, HAR, and EGARCH models in capturing the time-varying property of idiosyncratic volatility (IVOL). We find that the expected IVOL predictions by HAR are superior. In diverse portfolio scenarios, a greater degree of judgment is required to assess the pric...

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Published in: Review of Quantitative Finance and Accounting
ISSN: 0924-865X 1573-7179
Published: Springer Nature 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa66553
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spelling 2024-10-21T11:31:40.5862919 v2 66553 2024-05-31 Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models fb7fc71d3d6f93750bc475098b56778b 0009-0005-0018-1029 Chuxuan Xiao Chuxuan Xiao true false 2024-05-31 CBAE We investigate the performances of the ARFIMA, HAR, and EGARCH models in capturing the time-varying property of idiosyncratic volatility (IVOL). We find that the expected IVOL predictions by HAR are superior. In diverse portfolio scenarios, a greater degree of judgment is required to assess the pricing ability of expected IVOLs. For the lowest value-weighted quintiles and the expected IVOL estimated by the HAR model, the IVOL-return relationship is negative. Conversely, the IVOL-return relationship is positive for the expected IVOL estimated by the EGARCH model. Further evidence suggests a complicated and mixed relationship between the expected IVOL estimated by the ARFIMA model and stock returns. Journal Article Review of Quantitative Finance and Accounting 63 979 1006 Springer Nature 0924-865X 1573-7179 Asset Pricing; Idiosyncratic volatility; Time-varying; ARFIMA; HAR; EGARCH 1 10 2024 2024-10-01 10.1007/s11156-024-01279-z COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University SU Library paid the OA fee (TA Institutional Deal) Swansea University 2024-10-21T11:31:40.5862919 2024-05-31T15:57:02.8665336 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Chuxuan Xiao 0009-0005-0018-1029 1 Winifred Huang 0000-0002-8989-8595 2 David P. Newton 3 66553__30504__8192ae2306474543994975179f286b79.pdf 66553.VoR.pdf 2024-05-31T16:00:01.4280476 Output 1079562 application/pdf Version of Record true © The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License. true eng http://creativecommons.org/licenses/by/4.0/
title Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models
spellingShingle Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models
Chuxuan Xiao
title_short Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models
title_full Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models
title_fullStr Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models
title_full_unstemmed Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models
title_sort Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models
author_id_str_mv fb7fc71d3d6f93750bc475098b56778b
author_id_fullname_str_mv fb7fc71d3d6f93750bc475098b56778b_***_Chuxuan Xiao
author Chuxuan Xiao
author2 Chuxuan Xiao
Winifred Huang
David P. Newton
format Journal article
container_title Review of Quantitative Finance and Accounting
container_volume 63
container_start_page 979
publishDate 2024
institution Swansea University
issn 0924-865X
1573-7179
doi_str_mv 10.1007/s11156-024-01279-z
publisher Springer Nature
college_str Faculty of Humanities and Social Sciences
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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 performances of the ARFIMA, HAR, and EGARCH models in capturing the time-varying property of idiosyncratic volatility (IVOL). We find that the expected IVOL predictions by HAR are superior. In diverse portfolio scenarios, a greater degree of judgment is required to assess the pricing ability of expected IVOLs. For the lowest value-weighted quintiles and the expected IVOL estimated by the HAR model, the IVOL-return relationship is negative. Conversely, the IVOL-return relationship is positive for the expected IVOL estimated by the EGARCH model. Further evidence suggests a complicated and mixed relationship between the expected IVOL estimated by the ARFIMA model and stock returns.
published_date 2024-10-01T05:20:58Z
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score 11.09611

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