An overview of methods and problems in the analysis of time series data related to finance and insurance. The course will focus on both theory and application with real datasets using R and Python and will require writing reports. Topics include stationary processes, linear processes; elements of inference in time and frequency domains with applications; ARMA, ARIMA, SARIMA, ARCH, GARCH; filtering and smoothing time-series; and State-space models.