15.450 Analytics of Finance
Increased data availability and complexity creates the need for finance professionals who can work with data and can separate insights from noise. Introduces a set of modern analytical tools that specifically target finance applications. Exposure to statistical inference; financial time series; event study analysis; basic machine learning techniques for forecasting and working with big data. Aims to build operational models, take them to the data, and use real world data to build models for financial and macro forecasting, quantitative trading, and dynamic risk management. Looks behind the curtain of some fintech innovations, such as Kensho's "financial answer machine'' and big-data lending platforms. (Note: 15.457 is a more advanced version of 15.450. Students with solid background in statistics and proficient in programming are encouraged to take 15.457.)
15.450 will be offered this semester (Spring 2019). It is instructed by H. Chen.
Lecture occurs 1:00 PM to 2:30 PM on Tuesdays and Thursdays in E62-262.
This class counts for a total of 12 credits.
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