JORS 2021 Financial volatility modeling with option-implied information and important macro-factors.pdf (2.9 MB)
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Financial volatility modeling with option-implied information and important macro-factors

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journal contribution
posted on 15.09.2021, 15:15 by Stavroula YfantiStavroula Yfanti, Menelaos Karanasos
The research debate on the informational content embedded in option prices mostly approves the incremental predictive power of implied volatility estimates for financial volatility forecasting beyond that contained in GARCH and realized variance models. Contributing to this ongoing debate, we introduce the novel AIM-HEAVY model, a tetravariate system with asymmetries, option-implied volatility, and economic uncertainty variables beyond daily and intra-daily dispersion measures included in the benchmark HEAVY specification. We associate financial with macroeconomic uncertainties to explore the macro-financial linkages in the high-frequency domain. In this vein, we further focus on economic factors that exacerbate stock market volatility and represent major threats to financial stability. Hence, our findings are directly connected to the current world-wide Coronavirus outbreak. Financial volatilities are already close to their crisis-peaks amid the generalized fear about controversial economic policies to support societies and the financial system, especially in the case of the heavily criticized UK authorities’ delayed and limited response.

History

School

  • Business and Economics

Department

  • Business

Published in

Journal of the Operational Research Society

Publisher

Taylor & Francis

Version

VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by Taylor & Francis under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (CC BY-NC-ND 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

03/08/2021

Publication date

2021-08-23

Copyright date

2021

ISSN

0160-5682

eISSN

1476-9360

Language

en

Depositor

Dr Stavroula Yfanti. Deposit date: 10 September 2021