Student, who passed the course satisfactorily will be able to:

- generate pseudorandom numbers from a given distribution that is commonly used in finance and/or insurance
- apply Monte Carlo methods and variance reduction techniques to approximately integrate, or take, the underlying expectation and moments of random variables
- simulate continuous-time stochastic processes with continuous and discontinuous paths; characterise the convergence and rate of convergence of the numerical schemes used
- apply the methods to models in finance and/or insurance, such as pricing models under Black-Scholes or Heston model settings, interest rate models as well as derivatives, risk measures, pricing longevity products
- learn basics of Markov chain Monte Carlo methods and Bayesian estimation in actuarial mathematics