Capturing Downside Risk in Financial Markets

CG (Kees) Koedijk, R Pownall

Research output: Contribution to journalArticleAcademicpeer-review

50 Citations (Scopus)

Abstract

Using data on Asian equity markets, we observe that during periods of financial turmoil, deviations from the mean-variance framework become more severe, resulting in periods with additional downside risk to investors. Current risk management techniques failing to take this additional downside risk into account will underestimate the true Value-at-Risk with greater severity during periods of financial turnoil. We provide a conditional approach to the Value-at-Risk methodology, known as conditional VaR-x, which to capture the time variation of non-normalities allows for additional tail fatness in the distribution of expected returns. These conditional VaR-x estimates are then compared to those based on the RiskMetrics¿ methodology from J.P. Morgan, where we find that the model provides improved forecasts of the Value-at-Risk. We are therefore able to show that our conditional VaR-x estimates are better able to capture the nature of downside risk, particularly crucial in times of financial crises.
Original languageUndefined/Unknown
Pages (from-to)853-870
Number of pages18
JournalJournal of International Money and Finance
Volume18
Issue number6
DOIs
Publication statusPublished - 1999
Externally publishedYes

Research programs

  • RSM F&A

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