Ahelegbey, Daniel Felix (2022) Statistical Modelling of Downside Risk Spillovers. FinTech, 1 (2). pp. 125-134. DOI https://doi.org/10.3390/fintech1020009
Ahelegbey, Daniel Felix (2022) Statistical Modelling of Downside Risk Spillovers. FinTech, 1 (2). pp. 125-134. DOI https://doi.org/10.3390/fintech1020009
Ahelegbey, Daniel Felix (2022) Statistical Modelling of Downside Risk Spillovers. FinTech, 1 (2). pp. 125-134. DOI https://doi.org/10.3390/fintech1020009
Abstract
We study the sensitivity of stock returns to the tail risk of major equity market indices, including the G10 countries. We model the sensitivity relationship via extreme downside hedging and estimate the parameters via a Bayesian graph structural learning method. The empirical application examines whether downside risk connections among the major stock markets are merely anecdotal or provide a signal of contagion and the nature of sensitivity among major equity markets during the global financial crisis and the coronavirus pandemic. The result showed that the COVID-19 crisis recorded the historically highest spike in the downside risk interconnectedness among the major equity market indices, suggesting higher financial market vulnerability in the coronavirus pandemic than during the global financial crisis.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Bayesian inference; contagion; expected shortfalls; downside risk; financial crises; financial networks; COVID-19 pandemic |
Divisions: | Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 28 Mar 2025 15:53 |
Last Modified: | 28 Mar 2025 15:54 |
URI: | http://repository.essex.ac.uk/id/eprint/36639 |
Available files
Filename: 2022_FinTech Statistical Modelling of Downside Risk Spillovers.pdf
Licence: Creative Commons: Attribution 4.0