Quantitative Risk Management: VaR Estimation and Multivariate Distributions

Related lectures (31)

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Covers the construction of confidence intervals for a normal distribution with unknown mean and variance.

Discusses Monte Carlo VaR accuracy, confidence intervals, backtesting, and multivariate distributions.

Explores bias, variance, unbiased estimators, and confidence intervals in statistical estimation.

Explores bias, variance, and confidence intervals in parameter estimation using examples and distributions.

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.

Explores confidence intervals, hypothesis testing, and decision-making using test statistics and p-values.

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

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

Explores constructing confidence intervals and MLE limit theorems for large samples.