Reading for 25 April:

- Lo and MacKinlay: Chapters 8, 9

Princeton University Press Online Edition

- Sean D. Campbell, A Review of Backtesting and Backtesting Procedures
- Paul Cohen, (Alternate link)

Reading for 11 April:

- José Vidal, Fundamentals of Multiagent Systems, Chapter 1.
- Palmer et al., An Artificial Stock Market, Artif. Life Robotics (1999) 3:27-31
- Kendall and Su, The Co-Evolution of Trading Strategies in a Multi-Agent Based Simulated Stock Market...
- LeBaron, Agent-based computational finance: Suggested readings and early research, J. Economic Dynamics and Control (2000) 24:679-702
- van den Bergh et al., On Intelligent-Agent Based Analysis of Financial Markets

An afterthought from our risk class on 4 April:

- Read Michael Lewis' brief article on the Black-Scholes pricing model.
*Beware: the opinions expressed in this article are not necessarily those of this course or the university!*Click here for a PDF version.

Reading for 21 March:

- Bolland and Connor, A Constrained Neural Network Kalman Filter for Price Estimation in High Frequency Financial Data
- Zhuang and Chan, Volatility Forecasts in Financial Time Series with HMM-GARCH Models
- O, Lee, Park and Zhang, Stock Trading by Modelling Price Trend with Dynamic Bayesian Networks

Reading for 14 March: The reading to prepare for the 14 March 2008 lecture is as follows:

- (Before class) Finish Kevin Murphy's tutorial on graphical models.
- (Before class) Welch and Bishop, An Introduction to the Kalman Filter
- (Before HW5) L. R. Rabiner, A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition, Proceedings of the IEEE, vol 77, no 2, 257--287, 1989.
- (Before HW5) T. Ryden, T. Terasvirta, and S. Asbrink, Stylized Facts of Daily Return Series and the Hidden Markov Model, J. Applied Econometrics, 13, 217--244, 1998.

There are 2 handouts about HW3 questions:

- Tal Levy's Handout on American vs. European Options
- Olivier Guéant's Handout on the relationship between interest rates and implied volatility

Reading for 7 March:

*The Economist,*Better than beta?- Charniak, Bayesian Networks Without Tears
- Heckerman, A tutorial on learning with Bayesian networks
- Shenoy and Shenoy, Bayesian Network Models of Portfolio Risk and Return
- Optional: Begin Kevin Murphy's tutorial on graphical models (up to but not including "Temporal Models")

Reading for 29 February:

There are two papers on artificial neural networks applied to finance, and one on ARCH/GARCH models for nonlinear time series, which will be revelant in our future reading.

- http://www.eecs.harvard.edu/~parkes/cs286r/spring08/reading3/Kaastra.pdf
- http://www.eecs.harvard.edu/~parkes/cs286r/spring08/reading3/ARCH.pdf
- http://www.eecs.harvard.edu/~parkes/cs286r/spring08/reading3/zhang01.pdf

Reading for 22 February:

- Linear Classifiers:

We will develop the linear classifiers in class. - Support Vector Machines
- Neural networks:

Reading for 15 February:

Voit: (PDF Part 1, PDF Part 2)

Chap 4, except 4.5.8 on volatility indices

Chap 5 : 5.1 to 5.4 and 5.6.4

Chap 7: 7.1 to 7.4

Your peers' submitted homeworks on asset classes from last week are not required reading.

Reading for 8 February:

- Voit, Chapters 1, 2

PDF Excerpt

You should study Chapter 2 as thoroughly as possible; while it is brief, it is crucial. Chapter 3 is optional this week.

- Taleb, Chapter 10

PDF, pp. 135-161 PDF, pp. 162-164 - Lo and MacKinlay: Introduction, Chapters 1, 2

PDF Excerpt

- [Now Optional for this week] Ross, Chapters 4-6

You will need to be familiar with the material in chapters 1-3.