Explores the consistency and asymptotic properties of the Maximum Likelihood Estimator, including challenges in proving its consistency and constructing MLE-like estimators.
Explores constructing confidence regions, inverting hypothesis tests, and the pivotal method, emphasizing the importance of likelihood methods in statistical inference.
Covers the fundamentals of financial risk management, including types of risk, historical developments, regulatory events, and the challenges in quantitative risk management.
Covers maximum likelihood estimation to estimate parameters by maximizing prediction accuracy, demonstrating through a simple example and discussing validity through hypothesis testing.
