Course Meeting Times

Lectures: 2 sessions / week, 1.5 hours / session

Recitations: 1 session / week, 1.5 hours / session

Course Description

This course covers the main quantitative methods of finance. The course covers three broad sets of topics: derivative pricing using stochastic calculus, dynamic optimization, and financial econometrics. The emphasis is on rigorous and in-depth development of the key techniques and their application to practical problems.


15.401 Finance Theory I is a prerequisite for this course. 15.437 Options and Futures Markets is a recommended co-requisite.

Rudimentary programming skills are necessary. Homework assignments involve computer implementation of quantitative methods in MATLAB®. Prior knowledge of MATLAB® is not required. In addition to formal prerequisites, the course assumes solid undergraduate-level background in calculus, probability, and statistics.


Group problem sets (6 total) 50%
Final exam 50%

Course Textbooks

[Back]= Back, Kerry. A Course in Derivative Securities: Introduction to Theory and Computation. New York, NY: Springer, 2005. ISBN: 9783540253730.

[CL&M]= Campbell, John Y., Andrew W. Lo, and A. Craig MacKinlay. The Econometrics of Financial Markets. Princeton, NJ: Princeton University Press, 1996. ISBN: 9780691043012.

[Cochrane]= Cochrane, John H. Asset Pricing. Revised ed. Princeton, NJ: Princeton University Press, 2005. ISBN: 9780691121376.

[D&S]= DeGroot, Morris, and Mark J. Schervish. Probability and Statistics. 3rd ed. Reading, MA: Addison-Wesley, 2002. ISBN: 9780201524888.

[Tsay]= Tsay, Ruey S. Analysis of Financial Time Series. 2nd ed. New York, NY: John Wiley & Sons, 2005. ISBN: 978047169074.

The lectures will include suggestions for additional readings for each topic. Since there is no single textbook covering all the relevant topics, several books will be used. [Back] covers topics in stochastic calculus and derivative pricing. [Tsay] covers time-series methods in financial econometrics, and is the most frequently used textbook. [Cochrane] and [CL&M] cover advanced topics in financial econometrics. [D&S] covers basic background in probability and statistics and can be used for review as necessary.

List of Topics

The class will cover the following core topics:

  • Absence of arbitrage and risk-neutral pricing;
  • Itô stochastic calculus, Black-Scholes model and extensions, interest rate models;
  • Dynamic programming, asset allocation, Merton's solution, numerical methods for dynamic portfolio choice;
  • Monte Carlo simulation for derivative pricing;
  • Maximum likelihood and quasi-maximum likelihood estimation;
  • Generalized method of moments (GMM) basics, regression as GMM, standard errors, delta-method;
  • Small-sample inference, bootstrap;
  • Volatility models, GARCH.

Advanced topics include:

  • Derivative pricing and dynamic portfolio choice;
  • Extensions of GARCH, MIDAS models, multivariate volatility models;
  • Exploiting return predictability.


3 Problem set 1 due
5 Problem set 2 due
6 Problem set 3 due
9 Problem set 4 due
11 Problem set 5 due
13 Problem set 6 due