Introduction to Financial Time Series Analysis

Catalog description

Course covers methods and techniques for estimating and forecasting time series in financial markets, banking, and financial services. Main topics covered include discrete stochastic processes, ARIMA, GARCH, cross-section time-series (CSTS), error correction model (ECM), vector autoregression (VAR), hazard rate and competing risk, Markov transition, and asymptotic single risk factor (ASRF) model. Examples of applications include estimating trading volume and security prices, forecasting default and payment rates, modeling the term structure, estimating bid and ask spreads, forecasting business volume and revenue, and predicting business variables based on macroeconomic variables.