Modelling Dependence with Copulas - IFOR
Modelling Dependence with Copulas - IFOR
Modelling Dependence with Copulas - IFOR
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Contents<br />
Contents<br />
1 Motivation 1<br />
2 <strong>Copulas</strong> 3<br />
2.1 Mathematical Introduction . . . . . . . . . . . . . . . . . . . . . . . 3<br />
2.2 Sklar’s Theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4<br />
2.3 The Fréchet-Hoeffding Bounds for Joint Distribution Functions . . . 5<br />
2.4 <strong>Copulas</strong> and Random Variables . . . . . . . . . . . . . . . . . . . . . 6<br />
3 <strong>Dependence</strong> 11<br />
3.1 Linear Correlation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11<br />
3.2 Perfect <strong>Dependence</strong> . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12<br />
3.3 Concordance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12<br />
3.3.1 Kendall’s tau . . . . . . . . . . . . . . . . . . . . . . . . . . . 12<br />
3.3.2 Spearman’s rho . . . . . . . . . . . . . . . . . . . . . . . . . . 14<br />
3.4 Tail <strong>Dependence</strong> . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17<br />
4 Techniques for Construction of Multivariate <strong>Copulas</strong> 21<br />
4.1 The Farlie-Gumbel-Morgenstern Family . . . . . . . . . . . . . . . . 21<br />
4.2 The Marshall-Olkin Family . . . . . . . . . . . . . . . . . . . . . . . 23<br />
5 Archimedean <strong>Copulas</strong> 29<br />
5.1 Convex Sums . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29<br />
5.2 Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30<br />
5.3 Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33<br />
5.3.1 Tail <strong>Dependence</strong> . . . . . . . . . . . . . . . . . . . . . . . . . 36<br />
5.4 Order . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37<br />
5.5 Multivariate Archimedean <strong>Copulas</strong> . . . . . . . . . . . . . . . . . . . 38<br />
6 Elliptical <strong>Copulas</strong> 45<br />
6.1 The Gaussian Copula . . . . . . . . . . . . . . . . . . . . . . . . . . 47<br />
6.2 The t-copula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48<br />
7 Extreme Value <strong>Copulas</strong> 53<br />
7.1 Univariate Extreme Value Theory. . . . . . . . . . . . . . . . . . . . 53<br />
7.2 Multivariate Extreme Value Theory . . . . . . . . . . . . . . . . . . 54<br />
8 Mixture of Extremal Distributions 59<br />
9 <strong>Modelling</strong> Extremal Events in Practice 67<br />
9.1 Pricing Risky Insurance Contracts . . . . . . . . . . . . . . . . . . . 67<br />
9.2 The Perfect Storm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73<br />
10 Conclusions 79<br />
11 Appendix 81<br />
11.1 Implementations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81<br />
11.2 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84<br />
Literature 87<br />
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