- Understand the fundamentals of copulas – Learn what copulas are, their mathematical properties, and their role in modeling dependence structures
- Explore Sklar’s Theorem – Understand how joint cumulative distribution functions (CDFs) decompose into marginal distributions and a copula function
- Learn different types of copulas – Study Gaussian, t-Student, Clayton, and Gumbel copulas and their characteristics
- Estimate copula parameters in R – Use the copula package to estimate copula parameters through statistical methods
- Perform goodness-of-fit tests – Assess the quality of fitted copula models using statistical criteria such as AIC, BIC, and log-likelihood
- Visualize copulas in R – Generate contour plots, 3D surfaces, and scatter plots to interpret dependence structures
- Simulate data using copulas – Use copulas to generate synthetic datasets that preserve the dependence structure of modeled data
- Analyze dependencies – Compute Kendall’s Tau, Spearman’s Rho, and tail dependence coefficients to measure both typical and extreme event correlations
I’m Dr Krzysztof Ozimek, and my courses are science-based, carefully designed, and draw on over 30 years of experience teaching advanced topics in quantitative finance and analytical tools.