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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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