This course introduces time series methodology to the MSCF students. Emphasis will be placed on the data analytic aspects related to financial applications, with a view toward development of quantitative trading strategies. Topics studied in this course include univariate ARIMA modeling, forecasting, seasonality, model identification and diagnostics. In addition, GARCH and stochastic volatility modeling will be covered. At the end of the course, trading strategy development based on these models will be discussed. Reference texts (not required): Brockwell & Davis, Introduction to Time Series and Forecasting, 2nd edition, Springer (2002); N.H. Chan, Time Series: Applications to Finance, Wiley (2002).Prerequisite: Probability 46-921, Statistical Inference 46-923, Statistical and Machine Learning Methods for Financial Data 46-926.
Lecture: 100min/wk and Recitation: 50min/wk