MSAN 604 - Time Series Analysis for Business and Finance (2)
A survey of the theory and application of time series models, with a particular emphasis on financial and business application (e.g., exchange rates, sales data, Value-at-Risk, etc.). Tools for model identification, estimation, and assessment of are developed in depth. Smoothing methods and trend/seasonal decomposition methods are covered as well, including moving average, exponential, Holt-Winters, and Lowess smoothing techniques. Finally, volatility clustering is modeled through ARCH, GARCH, EGARCH, and GARCH-in-mean specifications. Statistical packages include R and SAS.