Delves into the application of artificial intelligence in finance, exploring tools like neural networks and Bayesian techniques, successful use cases in fraud detection and robo-advisors, and the importance of interpretability in machine learning models.
Covers Likelihood Ratio Tests, their optimality, and extensions in hypothesis testing, including Wilks' Theorem and the relationship with Confidence Intervals.
