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Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models
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David P. Newton
Review of Quantitative Finance and Accounting, Volume: 63, Pages: 979 - 1006
Swansea University Author: Chuxuan Xiao
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© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License.
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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...
| Published in: | Review of Quantitative Finance and Accounting |
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| ISSN: | 0924-865X 1573-7179 |
| Published: |
Springer Nature
2024
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa66553 |
| 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 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. |
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| Keywords: |
Asset Pricing; Idiosyncratic volatility; Time-varying; ARFIMA; HAR; EGARCH |
| College: |
Faculty of Humanities and Social Sciences |
| Funders: |
Swansea University |
| Start Page: |
979 |
| End Page: |
1006 |