Statistical Methods in Finance credit:

4 Hours

Statistical tools that are fundamental for financial modeling, analyzing financial data and further studies in financial engineering. Topics include summary statistics, statistical plots, point estimation, accuracy and precision, confidence interval, Monte Carlo simulation, maximum likelihood estimation, normal mixture, resampling, hypothesis testing, simple linear regression, multiple linear regression, variable selection, regression diagnostics, autocorrelation, moving average models, filtering, autoregressive models, ARIMA, forecasting, and selected additional topics. Implementations are done using R. Credit is not given toward graduation for: Credit is not given for both IE 522 and SE 524 . Prerequisite: IE 300 and MATH 461 .