Fat Tails, Serial Dependence, and Implied Volatility Index Connections


Ellington, Michael ORCID: 0000-0003-0264-7572 (2022) Fat Tails, Serial Dependence, and Implied Volatility Index Connections. European Journal of Operational Research, 299 (2). pp. 768-779.

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Abstract

This paper accounts for fat tails and serial dependence for implied volatility index network connections among equity and commodity markets using Bayesian vector heterogeneous autoregressions. I analyse the information content of such connections over short-, medium- and long-horizons for predicting underlying asset returns and whether conventional asset pricing risk factors explain the variation of portfolios that sort on directional connections. Including network connections within the information set yields significant gains when forecasting underlying asset returns. Sorting underlying assets on directional connections shows that investors can hedge against temporary changes to investment opportunities at horizons of less than one month.

Item Type: Article
Uncontrolled Keywords: Finance, Network Analysis, Forecasting, Volatility Spillovers, Serial Dependence, Fat Tails
Divisions: Faculty of Humanities and Social Sciences > School of Management
Depositing User: Symplectic Admin
Date Deposited: 28 Sep 2021 15:55
Last Modified: 14 Dec 2023 11:19
DOI: 10.1016/j.ejor.2021.09.038
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3138563

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