Intertemporal Capital Asset Pricing Model (ICAPM). Comments on the CAPM and ICAPM. Arbitrage Pricing Theory (APT). John H. Cochrane, ASSET PRICING Revised Edition (Princeton University Press, Princeton, USA. and Oxford, UK ), pp. xi + , $ 2. develop, on my website bestthing.info research /Papers . Intertemporal Capital Asset Pricing Model (ICAPM)
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This page is devoted to the book Asset Pricing, and the corresponding online class. Jan Notes for MBA investments classes. Summary of background ( statistics, regression, time . Alas, no pdf of the published version is available. Frankfurter, George M., "John H. Cochrane, Asset Pricing (Revised Edition) , Princeton University Press, Princeton and Oxford () xi + pp., US$ 85,". Asset Pricing, by John H. Cochrane, Princeton University. Press, This, in turn, implies that the pdf of the HPR becomes more positively skewed the.
Read the rest of the paper. Skip section V, Youtube videos 6. Econometrics and GMM. Hansen, Lars Peter and Kenneth J.
Cochrane, John H. Read it at least three times. The first time through, just understand the notation and the statement of the theorems. Find the GMM estimate defined, standard errors, test statistics. Get ready to use GMM. The second time through, read the "if" part of the proofs. Understand the stationarity, ergodicity, etc.
They matter! Finally, try to read the proofs. Hansen and Singleton is the crucial application to the consumption based model.
GMM Notes is a written version of my notes for the lectures. It's not exactly one to one, I condensed the lectures. The lectures and pdfs of the whiteboards should be enough.
This is one place to turn if those are confusing, and hence just an optional resource. The Brief Parable of Overdifferencing is a good example for the "Choosing a W matrix" lecture, showing you how statistical efficiency can lead to bad estimators.
Youtube videos 7. My "textbook" treatment of the Fama-French model and what it means. Fama, Eugene F. The Econometrics of Classic Linear Models This week we'll study the econometrics of linear factor pricing models such as Fama and French. Readings Asset Pricing Ch. Youtube videos 9. Time-Series Predictability, Volatility, and Bubbles In this module, we'll study time series predictability in detail. Extensive notes.
Written out treatment of predictability, suitable for reading on its own not just as a backdrop to the lecture. Notes Lecture notes. A short version 19 pages with the same material and the main bullet points. My lecture notes.
Youtube videos Equity Premium, Macroeconomics, and Asset Pricing In this module, we'll study the connection between macroeconomics and asset pricing.
A more detailed list of topics: Summary; other approaches Readings Macro-Finance. I wrote this after the lecture, really summing up everthing in this lecture. Don't miss the Appendix on Recursive Utility. My lecture covered a lot of papers. Here are the original papers. They are not required reading for this class, as the lectures are self contained. But you do need to know just what the papers are you're learning about, and you should read these if you want to pursue the topic further.
Main points covered in the lectures Campbell, John Y. Cochrane , By Force of Habit: Constantinides, George M. This is the source of the graph and tables for the "Production" section. This is the source of the "Dark Matter" quip from the lecture on recursive utility.
A recent paper I mentioned in lecture that uses the Constantinides-Duffie mechanism, adding rare disasters to individual risks.
Many references will allow you to quickly move back and catch up with the current literature Cochrane, John H. Hunter, George G. Kaufman and Michael Pomerleano, Eds. MIT Press Alas, no pdf of the published version is available. This is the source of the graph linking the level of prices to volatility. This is the source of the graph shown in lecture and the problem set you solved a few weeks ago.
Cochrane John H. Asset Pricing
Note, I left out a lot! There is a whole resurgent interest in "rare disasters" that I have not covered. Some of this is an attempt to understand the financial crisis, a worthy subject.
The big question is whether such frictions are important for every day asset pricing.
Option Pricing In this module, we'll discuss option pricing, the Black-Scholes option-pricing formula, and empirical option pricing. Required Reading Asset Pricing Chapter Bonds In this module, we'll discuss bonds and models of the term structure of interest rates.
Optional Reading Cochrane, John H. Unless, of course, everything is i. Problems for Chapter 9? This is a case where? If there were a? In an in? Intuitively, there are no arbitrage portfolios of stocks — portfolios that dominate in every state of nature.
Problems like this generate arbitrage bounds in option pricing problems. In option pricing, though, there are strictly dominating portfolios; a call option is better in every state of nature than the portfolio that holds the stock and borrows the strike payment. No, it has to be the risk free rate, or a zero-beta rate.
Rf You can di? The question is whether we can do this on the right hand side too. Can we write the CAPM in terms of an excess return on the right hand side? Rj E Rm? Once posed, you can see that the answer is no.
Betas are not linear in the denominator. Though the riskiness of the T bill rate does not matter for the left hand side, it does for the right. E xt xt? Write the autocorrelation coe?
E [xt xt?
E x2 cov xt xt? The S matrix is The standard error is xt xt? If the series is i. Of course, you can calculate standard errors without mean zero, and without i. You can do the correlation coe? E xt ,yt? The general formula: I think I meant in 2 to correct for heteroskedasticity but not autocorrelation, in which case the answer is? Thus, E ut ut?
Yes, even if returns are predictable. The test assets can be risky return di? Rf implies? Rf but not E Ri? Betas add in the left hand variable, but not in the right hand variable. The GRS test requires factors that are returns. Pricing errors can be correlated with betas with time-series regressions.
Not with a cross-sectional OLS regression. Cross-sectional regressions set the right hand variable — betas — orthogonal to the error term — alphas. They can again be correlated with a GLS cross-sectional regression. The cross-sectional regression with an intercept sets the average pricing error to zero. The pricing error of the equally weighted portfolio is, of course, the average pricing error.
This regression does not necessarily pass through the origin or risk free rate. E f and K is the number of factors. It is best to reserve d for the d matrix, and the two are no longer equal. The general formula?? However, the factors need not be unpredictable, and may comove with the pricing errors, so no further simpli? IK ad ad? T This is the standard formula for the variance of the sample mean.
The remaining terms add the e? Next, we want to test the pricing errors. T cov gT? We have ad? Then I? Cb b0 0 0 Under the null, E Re? Since the E f moment is zero in every sample, the last K diagonal elements of cov gT are zero. This is natural, since the E f moments are set to zero in each sample. To see this, de?
The vector of such betas across all factors is s?
A factor that is a return will have a single regression beta of one on itself, but will also have nonzero single regression betas on the other correlated factors. E f t and slope coe? The likelihood surface is? This intuitively appealing procedure is exactly a cross-sectional regression.
But it would be ad-hoc, not ML. Write the statistical model as just the assumption that individual returns and the market return are jointly normal, "? To make it easy, use only one test asset you can use the partitioned matrix inverse formulas to do the same thing with many test assets "?
You might want to exercise American puts early. Retrace the steps in the integral derivation of the Black-Scholes formula and show that the dw does not a? Evaluating it, Z e?
Thus, we multiply both terms of the Black-Scholes formula by 1, which does not change them. From Go back to the derivation on p. We start with pt? E rt It? However, b The results will depend on the information set you choose. Adding more variables to a VAR can change the fraction of return variance attributed to the di?
Fama and Bliss See the term structure chapter for notation. The basic idea, is that there is a mechanical connection between the? As you can see, the expectations hypothesis — expected returns the same for the? You can also see that as we change the?
(b) Substitute recursively,
Now, to express the same idea formally. This should remind you of the Campbell Shiller identity that you can discount a stock price by its ex-post returns. The left hand variable is the forward-spot spread in the Fama Bliss regression. The right hand term is the change in one year yield, and the holding period return on two year bonds. Now run a 27?
The left hand side is 1 — forward spot on forward spot. The right hand side gives the coe?
Imagine simulating out a huge number of data points from the VAR. Then, take only the return data, ignoring data on other variables. Run a regression of returns on lagged returns. You just have to go through and do for prices what we did for returns.
The equation for prices is, from Thus, the system — analogous to the equations in the middle of p. More about this book Co-Winner of the Paul A. The clever intuition and informal writing style make it a joy to read. Like a star athlete does with the sport, Cochrane makes it look easier than it really is.
This book was already a classic among finance scholars and on Ph. It will also prove highly useful to practitioners who seek an in-depth introduction to these tools. It will help experts in the field to consolidate their knowledge and beginners to appreciate the unity of asset pricing theory. Cochrane uses his mastery of the subject to present it in a clear and compelling manner that is easily accessible. It is a serious scholarly monograph, of interest to those who are working to advance financial theory, and it can also serve as a textbook in an advanced finance course.
It is thoughtful, inductive, and comprehensive. Shiller, author of Irrational Exuberance "This is a sparkling, intuitive, makes-it-look-easier-than-it really-is, gem of a book. Cochrane's focus is the classical asset pricing models of frictionless markets and rational expectations.These arbitrage bounds disappear if one posits a distribution in which it is always possible for each security to underperform the other.
If markets are complete — if he can also download and sell claims to the individual dividends — then he can do even more. Time-Series Predictability, Volatility, and Bubbles In this module, we'll study time series predictability in detail. Cochrane J. It is the? This intuitively appealing procedure is exactly a cross-sectional regression. Don't miss the Appendix on Recursive Utility.
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