Website for 35904 Asset Pricing

John H. Cochrane, Fall 2007

Last update 11/21/07

I. Announcements:

Please send me an email if you are going to take the class, but will not be registered as a GSB student (or even if you are, just to be sure). I want to build an email list of students in the class so I can send announcements.

It’s important to hit “Refresh” on your browser so you see any new items here, not the version of the webpage in your cache.

Class meets MW 3-5 in HC07.  The final exam is on Wed Dec 5 3-6 in HC07. You must take the exam at this time.

New: 9/26 There will be a review in C09 Fridays 12-1. No new material, this is just a time to get together with Alexi and talk about problem set, lecture, the meaning of life, etc.

II. Course Policies

This course is a survey of asset pricing theory, emphasizing a discount-factor and GMM approach. The discount factor is a unifying framework: p=E(mx) covers everything, stocks, bonds, options, real investments, discrete time, continuous time, asset pricing, portfolio theory, etc.

The course requirements are 1) Show up, read the book and papers, and participate in class discussion. 2) Do problem sets. 4) Take a final exam. The grade will be based on max(25% problem sets + 75% exam, 100% exam) plus class participation.  If you want me to learn your name and get class participation credit bring a name card and use it. If you don’t bring a name card to class and get your picture in the GSB facebook, don’t complain that faculty don’t know who you are. You may help each other on problem sets, but I expect everyone to actually do the work. MBAs may work in groups. You may not hand in problem sets late.

 Prerequisites. I design the course for GSB PhD students who have taken a year of PhD level economics and econometrics, fulfilling the "basic discipline" and "coordinated sequence" requirements with either economics or statistics. I also plan for economics department students who have taken the core exam. I encourage students to take 35901 (Fama) before or with this class. Facts motivate theory, and that background will make all this fall into place much better.

In general, you should have some Ph.D.-level macroeconomics, finance or statistics/econometrics before taking this course. I will use without much fanfare concepts like a representative consumer and dynamic program (macroeconomics); expected returns, betas, and facts about returns like predictability (finance); and basic time series tools like autocorrelations, VAR models, diffusion models. MBA students are welcome, with the understanding that the course assumes the above background.

There is one required text: Asset Pricing, Princeton University Press. I will post additional readings on the class website. I recommend the Revised Edition of Asset Pricing since I got rid of the typos, but you can use the first edition if you already have it and want to save some money. Here’s the Typo list for first edition of Asset Pricing. (If you’re using the second edition, these have all been fixed)

Communication:  Everything will be posted on the class website.  Make sure you sign up for the email list so you get news about typos etc.. I’m in  HC 459, 702-3059, john.cochrane@gsb.uchicago.edu

II. Schedule and reading list:

Please do the indicated required readings before class. 

Week 0. Vital Background Reading

1.      You need to be comfortable with time series mechanics. Start with the Appendix on Continuous time in Asset Pricing, p.489-496. Read the  Continuous time review notes for a quick refresher on dz and dt. I will use dz and dt on the first day, so make sure you understand this. (I won’t use the forward and backward equations right away.)  My Time series notes are a more leisurely refresher of discrete-time time-series mechanics.

2.      You need to know facts: predictability, value premium, etc., especially if you haven’t taken Fama’s class yet.  Read Asset Pricing Ch 20 389-393, and 426-454 to have some idea of why we're doing all this stuff. Section 2 of Financial Markets and the Real Economy p. 244-256 is a recent simpler treatment.  (New Facts in Finance  is an earlier somewhat simpler treatment of the same material.)

3.      If you don’t know it already, read one classic paper: Fama and French, “Multifactor explanations of asset pricing anomalies”. We’ll talk a lot about the “Fama-French three factor model” as the paradigm of current multifactor models in expected return-beta form.

Week 1. Basic model, Overview, Equity premium.

1.      Asset Pricing Ch1-2 and Ch 21.1 for equity premium

2.       (Optional) The classic paper: Lucas, Robert E. Jr, 1978, “Asset Prices in An Exchange Economy’’ Econometrica 46, 1429-1455.  This is the famous paper that launched the consumption-based model and endowment-economy framework.

Week 2. Contingent claims, state-space representation and existence of a discount factor 

1.      Asset Pricing Ch. 3-4

2.      (Optional) Week 2-3 also read Hansen, Lars Peter and Scott F. Richard, 1987, “The Role of Conditioning Information in Deducing Testable Restrictions Implied by Dynamic Asset Pricing Models” Econometrica 55, 587-613. This is the paper that sets out all of the state space stuff, and the conditional vs. unconditional mean variance frontier. It has all the assumptions and the proofs. Very dense, and I mean that as a compliment.

Week 3. Mean-variance frontier, beta representations, conditioning information.

1.      Asset Pricing Ch 5-8.

Week 4. Factor pricing models.; CAPM, ICAPM, APT

1.      Asset Pricing Ch.8-9.

Week 5. GMM 

1.      Asset Pricing Ch 10-11.

2.      (Optional) Hansen, Lars Peter, 1982, “Large Sample Properties of Generalized Method of Moments Estimators” Econometrica 50, 1029-1054. This paper has the GMM distribution theory and assumptions. Read along with Ch. 11 of Asset Pricing.

3.      (Optional)  Hansen, Lars Peter, and Kenneth J. Singleton, 1982, “Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models” Econometrical 50 1269-1286.; Errata  Applies GMM to the consumption-based model. The “how-to” paper accompanying the last paper. The Errata tables are the right ones. Notice the equity premium puzzle in the stock-bond estimation. Moral: plot your data.

Week 6. Regression tests, GRS, and GMM 

1.      Asset Pricing Ch 12-16

2.      (Optional) Fama and French, “Multifactor explanations of asset pricing anomalies”. A good paper to keep in mind as an application of all this technique. I’ll focus on the basic tests in Tables 1-2 as the classic example of "how to do cross-sectional tests."

Week 7. a) Option pricing and b) Term structure definitions, expectations hypothesis and factor structure. 

1.      Asset Pricing Ch 17; Ch. 19-1-19.3. Read the definitions, put call parity, yield, forward rate etc. carefully, as I won’t review that in class.

2.      Cochrane, John and Monika Piazzesi, “Bond Risk Premia”, American Economic Review

Week 8. Term structure models

1.      Asset Pricing Ch. 19

2.      Appendix to Cochrane and Piazzesi, Section D, “Affine Model’’ p. 19-31

3.      Lecture notes. Part 1 Part 2

Week 9. Portfolio theory. 

1.      Cochrane, John “Portfolio Theory” Notes

Optional:        

2.      Cochrane, John H. 1999, “Portfolio Advice for a Multifactor WorldEconomic Perspectives Federal Reserve Bank of Chicago 23 (3) 59-78. #6156

3.      Portfolio notes for MBA class. (Lots of practical stuff that didn’t make it in to the last two)

Week 10  Alternative utility functions: multiple goods, aggregation, habits, durable goods, labor, recursive utility, long run, etc. 

1.      Asset Pricing Ch 21.2

2.      Sections 4 and 6 of  Financial Markets and the Real Economy p.267-290, 302-314.

(Optional) My webpage. Of course you should read everything on this!

 

III. Problem sets

Problem set 1

Problem set 1 answers

 

Problem set 2

Problem set 2 answers

 

Problem set 3 

Problem set 3 Answers

 

Problem set 4

Problem set 4 answers

 

Problem set 5 Due Wednesday, not Monday.

Problem set 5 data

Problem set 5 Answers

Matlab program functions: doit min2

 

Problem set 6 Due Monday Nov 12.

Fama French Factors; Fama French Portfolios

Problem set 6 Answers

Matlab program. Functions olsgmm, tsregress_gmm, cs_gmm

 

Problem set 7

Option data. Bond data

Problem set 7 answers

 

Problem set 8

Problem set 8 Answers

 

Final exam from last time I taught this course. Warning: this may be useful to get some sense of my exam style. It’s probably not useful as a study guide, since I emphasized different topics this year. I’m not sure some of these are that great exam questions either. No, I will not post answers.