This course aims at introducing quantitative methods and techniques for time series modelling, analysing, and forecasting economic and business data.  Hypothesis tests for identifying the underlying serial correlation structure will be covered.  Various foundational models such as autoregressive and distribution lags (ARDL), autoregressive integrated moving average model (ARIMA), vector autoregressive model (VAR) and Error Correction models (EC), generalised autoregressive conditional heteroskedasticity models (ARCH and GARCH) will be discussed.  Students will learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques.