arXiv 31 Aug 2023 · Finance — Statistical Finance
arXiv:2309.00025 · PDF · DOI · OpenAlex · Extracted main text
We propose a set of dependence measures that are non-linear, local, invariant to a wide range of transformations on the marginals, can show tail and risk asymmetries, are always well-defined, are easy to estimate and can be used on any dataset. We propose a nonparametric estimator and prove its consistency and asymptotic normality. Thereby we significantly improve on existing (extreme) dependence measures used in asset pricing and statistics. To show practical utility, we use these measures on high-frequency stock return data around market distress events such as the 2010 Flash Crash and during the GFC. Contrary to ubiquitously used correlations we find that our measures clearly show tail asymmetry, non-linearity, lack of diversification and endogenous buildup of risks present during these distress events. Additionally, our measures anticipate large (joint) losses during the Flash Crash while also anticipating the bounce back and flagging the subsequent market fragility. Our findings have implications for risk management, portfolio construction and hedging at any frequency.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Dhaene, J., Linders, D., Schoutens, W., and Vyncke, D (2012) The Herd Behavior Index: A new measure for the implied degree of co-movement in stock markets | 1.000 | 6 | 3 | 100% |
| 2 | Ang, A. and Chen, J (2002) Asymmetric correlations of equity portfolios | 0.874 | 7 | 2 | 100% |
| 3 | Bernardi, M., Durante, F., and Jaworski, P (2017) CoVaR of families of copulas | 0.874 | 5 | 2 | 100% |
| 4 | Longin, F. and Solnik, B (2001) Extreme correlation of international equity markets | 0.874 | 5 | 2 | 100% |
| 5 | Inghelbrecht, K., Verdickt, G., Linders, D., and Xie, Y (2022) Model-free implied dependence and the cross-section of returns | 0.874 | 5 | 2 | 100% |
| 6 | Menkveld, A. J. and Yueshen, B. Z (2019) The flash crash: A cautionary tale about highly fragmented markets | 0.874 | 5 | 2 | 100% |
| 7 | Gijbels, I., Kika, V., and Omelka, M (2021) On the specification of multivariate association measures and their behaviour with increasing dimension | 0.843 | 4 | 4 | 75% |
| 8 | Hofert, M., Kojadinovic, I., Mächler, M., and Yan, J (2019) Elements of Copula Modeling with R | 0.843 | 4 | 3 | 75% |
| 9 | Nelsen, R (2007) An Introduction to Copulas | 0.822 | 6 | 2 | 83% |
| 10 | Hauksson, H., Dacorogna, M., Domenig, T., Mller, U., and Samorodnits… (2001) Multivariate extremes, aggregation and risk estimation | 0.811 | 4 | 2 | 100% |
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