Lecture
This lecture introduces the stochastic simulations course, covering the organization, course material, and motivating examples. It delves into the G/G/1 queueing model, discussing the arrival, waiting, and service times of customers, as well as the theoretical and practical aspects of simulating such a system. Additionally, it explores computational finance topics like insurance risk models and option pricing, computational statistics concepts such as likelihood ratio tests, and computational physics applications like the Ising model. The course content includes random variable generation, Monte Carlo methods, variance reduction techniques, Markov Chain Monte Carlo methods, and more.