Statistics and Financial Data Analysis (2019-2020)

Dr Katia Babbar
Course Term: 
Course Overview: 

A key part of modern finance is the analysis of financial time series. This course aims to introduce the basics of the statistical tools required in the analysis of financial data.

Course Syllabus: 

Maximum likelihood estimation and Fisher information theory. Standard estimation cases. Linear regression with normal and non-normal data. Transformations, weighted regression and heteroskedasticity. Polynomial bases and splines for curve fitting. Autoregressive models, calibration and autocorrelation structure. Order identification using AIC and BIC. Forecasting methods. Model checking. Moving Average models and calibration. ARMA modelling. Stationarity and spectral theory of the difference operator. Unit-root tests. ARIMA models. Connections to continuous time. Introduction to ARCH and GARCH modelling and calibration.