Data Mining in Finance (Andreas S. Weigend, Spring 1999)

Related Courses at Stern

 

In general, for a wealth of interesting courses, please visit the list of courses in the Finance Department, and the complete list of all Stern courses and syllabi. 

More specifically for this course, in addition to calculus and probability and the IS, Finance and Statistics core courses, Data Mining in Finance uses material from the following two courses: 

  • Statistical Inference and Regression Analysis (B90.3302) (the second half of B90.3302 is particularly important), 
  • Regression and Multivariate Data Analysis (B90.2301 = B90.3311 for PhDs ). 

Furthermore, 

  • Forecasting Time Series Data (B90.2302 = B90.3312 for PhDs = C22.0018 for undergraduates), or another time series course, 

can provide a useful background for the prediction part of this course. 

Deeper insights can be gained if this course is taken after or at the same time with: 

  • Bayesian Inference and Statistical Decision Theory (B90.3305), and/or 
  • Stochastic Processes I (B90.3321). 

Comparing this course to related IS courses, this course is statistically more advanced than 

  • Knowledge Systems in Organizations (B20.3336 = C20.3336), 

and also more theoretical, and covering a larger area, than 

  • Risk Management Systems (B20.3351). 

A more detailed general description includes the teaching philosophy. Furthermore, the book chapter Data Mining in Finance: Report from the Post-NNCM-96 Workshop on Teaching Computer Intensive Methods for Financial Modeling and Data Analysis (as pdf, as ps) provides some history of this course. 

 

Please address comments and questions to Andreas S. Weigend at aweigend@stern.nyu.edu.