John Cochrane Spring 2015 Asset Pricing PhD Class (Stanford Edition)

Last update 5/23/2015

Update: June 1 class will be a writing workshop. If you have not received email, contact me.

Class structure

I will be teaching three weeks of this class, April 6, April 13, and June 1.

This class will be integrated with three weeks of my coursera online course. You must sign up for the coursera class Asset Pricing Part 2 (be careful not to sign up for part 1!). You do not need to get a "certificate." Just "join for free". Do this right away! If you have technical problems you can email the coursera TAs Adam Jorring (Chicago) or Nina Karnaukh (St. Gallen).

Send me an email at with your email, username or whatever other identifying information you give coursera so we can pick your results out from the others. There is a special discussion forum for you.

Each week, do the corresponding coursera work before class. That involves watching some video lectures and doing some quizzes and homeworks.

The point of doing coursera first is that it will free me from lecturing on standard material, and will free us up to have a more freewheeling class discussion. Come to class prepared to present and to discuss the material. It also will free us to talk about the more advanced readings given below.

All readings have links. Please report broken links. Some links are to jstor or sciencedirect, which want an institutional login or vpn connection. If they ask for money, that's the problem.

You need access to my book, Asset Pricing, Princeton University Press, Revised Edition. The old edition is full of typos, so I recommend the revised edition. It's available at

Week 1 (April 6) Characteristics and the cross section of returns.

Rrequired readings. Focus on the tables and facts.

Optional. Additional review or textbook treatments (FYI, and some overlap)

Reference readings. I'll show the main tables of these as a tour of what's going on in current research.

Given time I will touch on this lightly beyond the coursera treatment. Jonathan will spend two weeks on it.

Week 2. (April 9) Time-Series predictability, volatility, and bubbles.

Required Readings.

Reference readings. The papers covered in the lecture, and things I'll talk about these in class.

Week 3. (June 1) Equity Premium and macro/asset Pricing without financial frictions.

Required Readings. Our assigned readings will be summaries and reviews, all covered in the coursera lectures.

The underlying papers follow. I don't expect you to read every word! But I also don't want you to think I'm making up my characterization of these papers.

Additional Readings

If you get interested in pursuing any of the topics, or if you're looking for an interesting replication or extension project, here is a list of papers I think are interesting in these literatures.

All of my asset pricing papers are on my research webpage. The "Grumpy economist finance collection may also be a useful source of topics.

Week 1 Additional Readings and References

Dissecting momentum. Warning, though attractive to dissect momentum, and though there is no really good answer, a lot of people are ahead of you.

Additional or review papers on size, value, momentum

  1. Davis, James, Eugene F. Fama, and Kenneth R. French 2000, "Characteristics, Covariances, and Average Returns: 1929 to 1997" Journal of Finance 55 389-406. Our problem set suggests that the characteristics (size, b/m) are more powerful predictors of returns than the betas. There's nothing wrong with that; betas are not perfectly measured. Still, is it true? Here's FF's view of the issue.
  2. Fama, Eugene F. and Kenneth R. French 2011 Size, Value and Momentum in International Stock Returns, Journal of Financial Economics 105 (2012) 457?472. Always read the latest Fama French paper on anything.

Additional Variables that forecast stock returns

More on betting against beta

  1. Andrea Frazzini and Lasse Heje Pedersen (2012) Embedded Leverage Extends the arugment in "Betting against beta." People like me objected, if people want leverage, let them buy options. The claim here, options also have too low expected returns. "Strong evidence from index options, equity options, and leveraged ETFs."
  2. Asness, Clifford, Andrea Frazzini and Lasse Heje Pedersen (2013) Low risk investing without industry bets Refutes the idea that by sorting on beta they are really sorting on industry.
  3. Novy-Marx, Robert, 2013, The Quality Dimension of Value Investing, More on earnings quality

300 forecasting variables! Really, aren't we fishing a bit?

  1. Campbell Harvey put together an excel spreadsheet with all 300 (!) variables claimed to forecast stock returns as of 2013. I found the link in his paper "...and the cross-section of expected returns" with Yan Lu. The paper makes the serious point that there is a lot of fishing going on.
  2. Novy-Marx, Robert, 2014, Predicting anomaly performance with politics, the weather, global warming, sunspots, and the stars Journal of Financial Economics 112, 137?146. Ungated draft. A colorful warning about fishing.
  3. Jonathan Lewellen 2013, "The cross section of expected stock returns" How well do these huge Fama MacBeth regressions of returns on to characteristics work out of sample?

Week 2 Additional Readings and References

Additional References

John Campbell Classics: The linearized present value relation, and some of his contributions to the stock predictability literature. These are important references for my lectures and notes on predictability

If you want to work on predictability, you need to catch up with Martin Lettau and Sydney Ludvigson's cay work. Start at Martin Lettau's Website. There are far more John Campbell papers than I have included here. Browse John Campbell's website.

Some high-frequency time-series return forcasters:

A longer reading list on empirical finance organized by topics. May be helpful for any thesis work.