VaR Model Evaluation

Related lectures (30)

Page 1 of 3

Covers the multivariate normal distribution, properties, and sampling methods.

Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.

Covers probability, statistics, independence, covariance, correlation, and random variables.

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Covers statistical concepts like probability, estimation, hypothesis testing, and confidence intervals for mathematicians.

Introduces multivariate statistics, covering normal distribution properties and characteristic functions.

Covers z Variable as a Delay Operator, realizable systems, probability theory, stochastic processes, and Hilbert Spaces.

Covers the construction of confidence intervals and approximate critical values in statistical inference.

Covers confidence intervals for Gaussian means, Student distribution, and Wald confidence intervals for maximum likelihood estimators.

Covers Value at Risk (VaR) and Expected Shortfall (ES) in risk management, including backtesting and multivariate distributions.