Copulas: Properties and Applications

Related lectures (29)

Page 3 of 3

Covers continuous random variables, probability density functions, and distributions, with practical examples.

Covers elliptical distributions, including properties, applications, and risk management implications.

Covers various probability distributions and their applications in real-world scenarios.

Covers conditional density, independence of random variables, expectation, and variance calculation.

Explores moment-generating functions, linear combinations, and normality of random variables.

Covers copulas, Sklar's Theorem, meta distributions, and various dependence measures like rank correlations and coefficients of tail dependence.

Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.

Covers the fundamentals of probability theory, including conditional probability, Bayes' rule, and random variables.

Covers random variables, probability functions, expectations, variances, and joint distributions.