This course aims to introduce quantitative methods and techniques for time series modelling, analysis, and forecasting of economic and business data. Topics include time series properties of fluctuation, cycle, seasonality, trend, unit roots tests for stationary. Models such as autoregressive and distribution lags, moving average and exponential smoothing, ARIMA, VAR and Error Correction (EC), ARCH and GARCH, Logit and Probit models will be discussed with both statistical theory and practical methods of model building and analysis. Emphasis will also be put on the applications in economic and business related areas. Computing is an integral part of this course, all students are required to do data analysis, modelling and forecasting with computer statistics software.