FE 2104661 - Statistical Method for Financial Engineering



Lecture notes

All handouts may contain some typo errors, which will be soon revised during the semester. The reviews on linear algebra, probability and statistics will NOT be taught in class. Students must review them before the lectures. Handouts of some chapters are not finished yet and will be added later.

  1. Course Overview
  2. Review on linear algebra (revised on 09/2016)
  3. Review on probability and statistics (revised on 5/10/2015)
  4. Estimators (revised on 8/26/2017)
  5. Linear regression (revised on 9/2016)
  6. Nonlinear estimators (MLE, NLS) (revised on 19/09/2016)
  7. Hypothesis tests (Wald, Likelikelihood tests) (revised on 8/27/2017)
  8. Model selection (revised on 19/10/2015)

The topics not taught this year

  1. Instrumental variables (revised on 31/08/2015)
  2. General methods of moments (revised on 5/10/2015)

Course Information

Lectures:Room 1104, Mon 6-9 PM
Instructor:Jitkomut Songsiri (JSS)
Course Syllabus:
 available here

Lecture handouts are mostly summarized from these two books:

      1. Cameron and P.K. Trivedi, Microeconometrics: Method and Applications, Cambridge, 2005
  • J.M. Wooldridge, Econometric Analysis of Cross Section and Panel Data, the MIT Press, 2010
  • W.H. Greene, Econometric Analysis, 7 th Edition, Pearson, 2012
Optional Textbooks:
  • Defusco, R., McLeavey, D., Pinto, J., and Runkle, D. Quantitative Investment Analysis, 2nd edition, Wiley, 2007
  • Rupert, D. Statistics and Data Analysis for Financial Engineering, Springer, 2012
  • Keller, G. Managerial Statistics, 9th edition. South-Western, Cengage Learning, 2012
  • Black, K. Applied Business Statistics, 7th edition. John Wiley and Sons, Inc. 2012
  • Anderson, D., Sweeney, D., and Williams, T. Statistics for Business and Economics,11th edition.South-Western, Cengage Learning, 2011
  • Mendenhall, W., Beaver, R.J., and Beaver, B.M. Introduction to Probability and Statistics, 12th edition. Thomson, 2006
  • Abraham, B. and Ledolter, J. Introduction to Regression Modelings, Duxbery, 2006
  • Kutner, Nachtsheim, Neter, and Li. Applied Linear Statistical Models, 5th edition. McGraw-Hill / Irwin, 2005
  • Kohler, H. Statistics for Business and Economics. South-Western, 2002
Grading:Homework 30% Midterm 35% Final 35%
Softwares:Most assignments will involve MATLAB programming with optimization toolbox. Students should install CVX which is a MATLAB package for solving convex programs.