Dynamic Copula Methods in Finance -- Contents -- Preface -- 1 Correlation Risk in Finance -- 1.1 Correlation Risk in Pricing and Risk Management -- 1.2 Implied vs Realized Correlation -- 1.3 Bottom-up vs Top-down Models -- 1.4 Copula Functions -- 1.5 Spatial and Temporal Dependence -- 1.6 Long-range Dependence -- 1.7 Multivariate GARCH Models -- 1.8 Copulas and Convolution -- 2 Copula Functions: The State of the Art -- 2.1 Copula Functions: The Basic Recipe -- 2.2 Market Co-movements -- 2.3 Delta Hedging Multivariate Digital Products -- 2.4 Linear Correlation -- 2.5 Rank Correlation -- 2.6 Multivariate Spearman's Rho -- 2.7 Survival Copulas and Radial Symmetry -- 2.8 Copula Volume and Survival Copulas -- 2.9 Tail Dependence -- 2.10 Long/Short Correlation -- 2.11 Families of Copulas -- 2.11.1 Elliptical Copulas -- 2.11.2 Archimedean Copulas -- 2.12 Kendall Function -- 2.13 Exchangeability -- 2.14 Hierarchical Copulas -- 2.15 Conditional Probability and Factor Copulas -- 2.16 Copula Density and Vine Copulas -- 2.17 Dynamic Copulas -- 2.17.1 Conditional Copulas -- 2.17.2 Pseudo-copulas -- 3 Copula Functions and Asset Price Dynamics -- 3.1 The Dynamics of Speculative Prices -- 3.2 Copulas and Markov Processes: The DNO approach -- 3.2.1 The * and Product Operators -- 3.2.2 Product Operators and Markov Processes -- 3.2.3 Self-similar Copulas -- 3.2.4 Simulating Markov Chains with Copulas -- 3.3 Time-changed Brownian Copulas -- 3.3.1 CEV Clock Brownian Copulas -- 3.3.2 VG Clock Brownian Copulas -- 3.4 Copulas and Martingale Processes -- 3.4.1 C-Convolution -- 3.4.2 Markov Processes with Independent Increments -- 3.4.3 Markov Processes with Dependent Increments -- 3.4.4 Extracting Dependent Increments in Markov Processes -- 3.4.5 Martingale Processes -- 3.5 Multivariate Processes -- 3.5.1 Multivariate Markov Processes.

3.5.2 Granger Causality and the Martingale Condition -- 4 Copula-based Econometrics of Dynamic Processes -- 4.1 Dynamic Copula Quantile Regressions -- 4.2 Copula-based Markov Processes: Non-linear Quantile Autoregression -- 4.3 Copula-based Markov Processes: Semi-parametric Estimation -- 4.4 Copula-based Markov Processes: Non-parametric Estimation -- 4.5 Copula-based Markov Processes: Mixing Properties -- 4.6 Persistence and Long Memory -- 4.7 C-convolution-based Markov Processes: The Likelihood Function -- 5 Multivariate Equity Products -- 5.1 Multivariate Equity Products -- 5.1.1 European Multivariate Equity Derivatives -- 5.1.2 Path-dependent Equity Derivatives -- 5.2 Recursions of Running Maxima and Minima -- 5.3 The Memory Feature -- 5.4 Risk-neutral Pricing Restrictions -- 5.5 Time-changed Brownian Copulas -- 5.6 Variance Swaps -- 5.7 Semi-parametric Pricing of Path-dependent Derivatives -- 5.8 The Multivariate Pricing Setting -- 5.9 H-Condition and Granger Causality -- 5.10 Multivariate Pricing Recursion -- 5.11 Hedging Multivariate Equity Derivatives -- 5.12 Correlation Swaps -- 5.13 The Term Structure of Multivariate Equity Derivatives -- 5.13.1 Altiplanos -- 5.13.2 Everest -- 5.13.3 Spread Options -- 6 Multivariate Credit Products -- 6.1 Credit Transfer Finance -- 6.1.1 Univariate Credit Transfer Products -- 6.1.2 Multivariate Credit Transfer Products -- 6.2 Credit Information: Equity vs CDS -- 6.3 Structural Models -- 6.3.1 Univariate Model: Credit Risk as a Put Option -- 6.3.2 Multivariate Model: Gaussian Copula -- 6.3.3 Large Portfolio Model: Vasicek Formula -- 6.4 Intensity-based Models -- 6.4.1 Univariate Model: Poisson and Cox Processes -- 6.4.2 Multivariate Model: Marshall-Olkin Copula -- 6.4.3 Homogeneous Model: Cuadras Augé Copula -- 6.5 Frailty Models -- 6.5.1 Multivariate Model: Archimedean Copulas.

6.5.2 Large Portfolio Model: Schönbucher Formula -- 6.6 Granularity Adjustment -- 6.7 Credit Portfolio Analysis -- 6.7.1 Semi-unsupervised Cluster Analysis: K-means -- 6.7.2 Unsupervised Cluster Analysis: Kohonen Self-organizing Maps -- 6.7.3 (Semi-)unsupervised Cluster Analysis: Hierarchical Correlation Model -- 6.8 Dynamic Analysis of Credit Risk Portfolios -- 7 Risk Capital Management -- 7.1 A Review of Value-at-Risk and Other Measures -- 7.2 Capital Aggregation and Allocation -- 7.2.1 Aggregation: C-Convolution -- 7.2.2 Allocation: Level Curves -- 7.2.3 Allocation with Constraints -- 7.3 Risk Measurement of Managed Portfolios -- 7.3.1 Henriksson-Merton Model -- 7.3.2 Semi-parametric Analysis of Managed Funds -- 7.3.3 Market-neutral Investments -- 7.4 Temporal Aggregation of Risk Measures -- 7.4.1 The Square-root Formula -- 7.4.2 Temporal Aggregation by C-convolution -- 8 Frontier Issues -- 8.1 Lévy Copulas -- 8.2 Pareto Copulas -- 8.3 Semi-martingale Copulas -- A Elements of Probability -- A.1 Elements of Measure Theory -- A.2 Integration -- A.2.1 Expected Values and Moments -- A.3 The Moment-generating Function or Laplace Transform -- A.4 The Characteristic Function -- A.5 Relevant Probability Distributions -- A.6 Random Vectors and Multivariate Distributions -- A.6.1 The Multivariate Normal Distribution -- A.7 Infinite Divisibility -- A.8 Convergence of Sequences of Random Variables -- A.8.1 The Strong Law of Large Numbers -- A.9 The Radon-Nikodym Derivative -- A.10 Conditional Expectation -- B Elements of Stochastic Processes Theory -- B.1 Stochastic Processes -- B.1.1 Filtrations -- B.1.2 Stopping Times -- B.2 Martingales -- B.3 Markov Processes -- B.4 Lévy Processes -- B.4.1 Subordinators -- B.5 Semi-martingales -- References -- Extra Reading -- Index.