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• W1493647213 abstract "This paper investigates the potential for extreme co-movements between financial assets by directly testing the underlying dependence structure. In particular, a t-dependence structure, derived from the Student t-distribution, is used as a proxy to test for this extremal behavior. Tests in three different markets (equities, currencies, and commodities) indicate that extreme co-movements are statistically significant. Moreover, the correlation-based Gaussian dependence structure, underlying the multivariate Normal distribution, is rejected with negligible error probability when tested against the t-dependence alternative. The economic significance of these results is illustrated via three examples: co-movements across the G5 equity markets; portfolio value-at-risk calculations; and, pricing credit derivatives. This paper investigates the potential for extreme co-movements between financial assets by directly testing the underlying dependence structure. In particular, a t-dependence structure, derived from the Student t-distribution, is used as a proxy to test for this extremal behavior. Using likelihood ratio-based methods, we show that the presence of extreme co-movements is statistically significant in three asset markets (equities, currencies, and commodities), as well as across international (G5) equity markets. In addition, this likelihood ratio test indicates that the correlation-based Gaussian dependence structure is not supported on the basis of observed asset co-movements. The economic significance and consequences of these results are illustrated via several examples." @default.
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• W1493647213 date "2002-01-01" @default.
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• W1493647213 title "Beyond Correlation: Extreme Co-movements Between Financial Assets" @default.
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• W1493647213 doi "https://doi.org/10.2139/ssrn.317122" @default.
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