Probabilistic and Stochastic Models in Business

This course is an advanced study of probability theory and an introduction to stochastic modeling and its applications in finance, economics and business analytics. Markov chains are widely used in many descriptive and prescriptive models, especially for describing the evolution and optimization of dynamic systems. Poisson processes are used for the enumeration of discrete events and are involved in queuing models and their applications in computer science, telecommunications, services, and transportation. Renewal processes are used in reliability and systematic maintenance. Brownian motions are the basis of several stochastic models used in finance. The concepts covered in this course are essential preparation for the fields of quantitative finance, stochastic optimization, and decision making under uncertainty.