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Economics 483
Introduction to Computational Finance and Financial Econometrics

Course Description

Eric Zivot
M228 Savery Hall
Office Hours: MF 10:30-11:30

Fall 2004

This course is an introduction to data analysis and econometric modeling using applications in finance. Equivalently, this course is an introduction to computational finance and financial econometrics.  As such, the course utilizes concepts from microeconomics, finance, mathematical optimization, data analysis, probability models, statistical analysis and econometrics.

The emphasis of the course will be on making the transition from an economic model of asset return behavior to an econometric model using real data. This involves: (1) specification of an economic model; (2) estimation of an econometric model; (3) testing of the assumptions of the econometric model; (4) testing the implications of the economic model; (5) forecasting from the econometric model. The modeling process requires the use of economic theory, probability models, optimization techniques and statistical analysis.

Topics in financial economics include asset return calculations, portfolio theory, index models, the capital asset pricing model and investment performance analysis. Mathematical topics covered include optimization methods involving equality and inequality constraints and basic matrix algebra. Statistical topics to be covered include  probability and statistics (expectation, joint distributions, covariance,  normal distribution, sampling distributions, estimation and hypothesis testing etc.) with the use of calculus, descriptive statistics and data analysis, linear regression, basic time series methods, the simulation of random data and resampling methods.

This course is one of the core courses for the new Graduate Certificate in Computational Finance.  It is an elective for the Undergraduate Certificate in Economic Theory and Quantitative Methods and one of the core courses for the new Certificate in Quantitative Managerial Economics.  It is also included in the Advanced Undergraduate Economic Theory and Quantitative Methods Courses list for the Bachelor of Science degree in Economics.

Note: This course is in the process of being renumbered and renamed in order to form a sequence of upper division courses in financial economics. The proposed new course number is Econ 424, and the proposed new name is Introduction to Computational Finance.  Econ 422 combined with Econ 424 provides a comprehensive introduction to the theory and practice of financial economics.

Course Requirements

  • Homework and Computer labs 25%: due at the beginning of class every Wednesday

  • Midterm exam 25%

  • Class project 25%

  • Final exam 25%

The homework, computer labs and project comprise the core of the course and have been weighted accordingly for grading purposes.  I believe that one cannot obtain an adequate knowledge and appreciation of model building, finance and econometrics without "getting one's hands dirty" in the computer lab.

Note: Homework assignments for the students taking the course as part of the Graduate Certificate in Computational Finance will be more difficult and more computationally intensive.


Formally, the prerequisites are Econ 300 and an introductory statistics course (Econ 311 or equivalent). Econ 482 (Econometric Theory) is not a prerequisite. More realistically, the ideal prerequisites are a year of calculus (through partial differentiation and constrained optimization using Lagrange multipliers), some familiarity with matrix algebra, a course in probability and statistics using calculus, intermediate microeconomics and an interest in financial economics (Econ 422 would be helpful).


Required Texts

  • Statistics and Finance: An Introduction, by David Ruppert, Springer-Verlag, New York.

  • An Introduction to Computational Finance and Financial Econometrics by Eric Zivot, manuscript in preparation (see the Notes page for preliminary chapters)

Recommended Texts

  • The Basics of S-PLUS, Third Edition, by Krause and Olson, Springer-Verlag, New York. Available for purchase from Insightful CorpThis is a very nice introduction to S-PLUS with lots of examples. A possible replacement for this book is David Smith's short-course notes on S-PLUS for finance. These are available for download:

  • Modern Portfolio Theory and Investment Analysis, Sixth Edition, by E.J. Elton and M.J. Gruber, Wiley, New York, 2002. This text gives a very detailed treatment of portfolio theory.

  • Financial Modeling, Second Edition,  by Simon Benninga. MIT Press, 2000. This textbook covers financial modeling using Microsoft Excel.

  • Statistical Analysis of Financial data in S-PLUS, by Rene Carmona, Springer-Verlag, 2004. This is a great book but is a bit too advanced for this course. It is used at Princeton in the Masters Program in Financial Engineering.

Note: All recommended texts will be placed on reserve at the library.


The course will utilize Microsoft Excel for spreadsheet modeling, and S-PLUS for data analysis and statistical modeling.

Excel is included with all version of Microsoft office, and is available on all PC computers around campus.

S-PLUS is a statistical modeling and graphical analysis program sold by Insightful Corporation (a local Seattle company), and is available on many computers throughout the UW campus. The CSSCR lab, in the basement of Savery Hall, has S-PLUS for windows (and the add-on modules) on most of the PCs. S-PLUS for UNIX is also available on some of the campus mainframe computers. Insightful provides a free student version of S-PLUS through e-academy. The University of Washington has an S-PLUS site license package, which allows students to purchase the full version of S-PLUS along with all add-on modules for $115. There is also a discount for purchases of 5-pack bundles ($475 per 5-pack).

There are several add-on modules for S-PLUS. We will utilize the S+FinMetrics module for some of the statistical analysis. This module is not included with the student version of S-PLUS, but is included in the S-PLUS site license package. It is available on the computers in the CSSCR lab, the Balmer Computer lab, the econ dept computer lab and the MSCC computer lab.

The book Modeling Financial Time Series with S-PLUS by Eric Zivot and Jiahui Wang, Springer-Verlag, serves as the User's Guide for S+FinMetrics. A non-printable .pdf version of the book is available from the Insightful website: Modeling Financial Time Series with S-PLUS