Wednesday, June 3, 2015
Asset Pricing Summer School
At least one university is going to use this more formally: Require completion of the class for their PhD students (either incoming or between first and second year,) and organize a TA and group meetings around the class. We have found that this sort of social organization helps a lot for students to get through online classes.
The course offers a free “certificate” for achieving a certain grade level in the class, which gives an incentive to actually do the problems. Faculty can tie achievement of the “certificate’ to whatever carrots and sticks they want to offer. For example, one instructor is going to treat achievement of the “certificate” as an assignment for his fall PhD class, and include it in the grade.
Since the class covers most of the basics, this structure may free a faculty member teaching next year to focus the PhD classes on more advanced material. It’s also useful as a “flipped classroom,” allowing the faculty member to spend less time on algebra and derivations, and more on intuition, extensions, and current research.
This session won’t have TAs on my part, though I will monitor the forums and attend to glitches as they crop up.
The class is free. To sign up or see the classes, follow these links
Part 1: https://www.coursera.org/course/assetpricing
Part 2: https://www.coursera.org/course/assetpricing2
The class experience consists of watching short lecture videos, doing the assigned reading, answering quzzes and fairly extensive problem sets, and taking an exam. The course has discussion forums which are quite useful.
The class starts next Monday, June 8. It is open for registration now, and will be open for students to see materials and start work by the end of the week. Part 1 (7 weeks) ends July 27, and Part 2 (7 weeks) ends Sept 14. The two parts may be taken independently. Students not wishing a grade may use these materials freely and just do whatever parts seem interesting. I've also set up the grading pretty flexibly to allow people to adjust their schedules rather than follow the week by week rigid schedule.
This is a bit late notice, but I hope blog readers will pass on notice to PhD students or prospective ones, and to faculty members who are teaching PhDs in the fall and might find this resource useful.
Week 1 Stochastic Calculus Introduction and Review. dz, dt and all that.
Week 2 Introduction and Overview. Challenging Facts and Basic Consumption-Based Model
Week 3 Classic issues in Finance. Equilibrium, Contingent Claims, Risk-Neutral Probabilities.
Week 4 State-Space Representation, Risk Sharing, Aggregation, Existence of a Discount Factor.
Week 5 Mean-Variance Frontier, Beta Representations, Conditioning Information.
Week 6 Factor Pricing Models -- CAPM, ICAPM and APT.
Week 7 Econometrics of Asset Pricing and GMM. Final Exam
Week 1 a) The Fama and French model b) Fund and performance evaluation.
Week 2 Econometrics of classic linear models.
Week 3 Time series predictability, volatility and bubbles.
Week 4 Equity premium, macroeconomics and asset pricing.
Week 5 Option Pricing.
Week 6 Term structure models and facts.
Week 7 Portfolio Theory and Final Exam