IE 522 - Statistical Methods in Finance
|Statistical Methods in Finance||IE522||B||77432||LCD||4||0930 - 1050||M W||144 Loomis Laboratory||Liming Feng|
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Statistics is the most important tool for analyzing financial data. IE 522 covers basic probability theory and statistical methods that are fundamental for financial modeling and analysis of financial data. This course is restricted to the Master of Science in Financial Engineering students. The materials that are covered include: probability basics (probability space, probability measure, conditional probability, random variable, probability distribution, expectation, commonly used distributions, characteristic function, multivariate distribution, conditional expectation); statistical inference (descriptive statistics, R, point estimation, Monte Carlo simulation, confidence interval, hypothesis testing, maximum likelihood estimation, likelihood ratio test, resampling, normal mixture); time series models (stationarity, autocorrelation, moving averaging process, autoregressive process, ARIMA models, parameter estimation, forecasting, ARCH and GARCH models); and linear regression (simple linear regression, ordinary least squares estimation, analysis of variance, goodness of fit, multiple linear regression, statistical inference, regression diagnostics). Credit is not given for both IE 522 and GE 524. Prerequisite: MATH 415.