Empirical Asset Pricing II

FIN512 Empirical Asset Pricing II

  • Topics


    Students should have a thorough understanding of the key topics discussed in the course. The asset pricing field is vast, but we will focus primarily on two core ideas:

    1. time-series properties of asset returns (predictability, volatility, correlations with other variables, etc.)
    2. cross-sectional properties of asset returns implied by equilibrium asset pricing models (including CAPM, consumption-based asset pricing, factor models, etc.)

    We will also examine the bond market and look at some simple term structure models, as well as the pricing of equity index derivative securities. Finally, we will discuss some recent research on the commodity futures markets. We will use a variety of econometric techniques, including GMM and maximum likelihood, as well as various time-series models. We view these econometric techniques as a way of answering economic questions, rather than being interested in the econometric methodology per se.

  • Learning outcome

    Learning outcome

    Students will be introduced to research in empirical asset pricing by reading and discussing research papers. Some papers are classics in the field, while some are more recent and highlight the current questions and issues in the field. The course will give the students the necessary foundation to read, synthesize, and critically analyze articles published in the field´s top tier journals. Further, the students will learn how econometric techniques, such as time-series and cross-sectional regressions and the Generalized Method of Moments, that are typically implemented in current research. The course should provide participants with an overview of key theories and recent trends in empirical asset pricing.

    Knowledge - The candidate...

    • is in the forefront of knowledge within contemporary topics in empirical asset pricing
    • can evaluate the expediency and application of different methods and processes for conducting empirical research in this area
    • can contribute to the development of new knowledge, new theories and methods in empirical asset pricing

    Skills ¿ The candidate...

    • can formulate problems, plan and carry out empirical research within the domain of empirical asset pricing
    • can carry out research and scholarly research work of a high international standard and be able to publish in international peer reviewed finance journals
    • can handle complex academic issues and challenge established knowledge in asset pricing

    Competence - The candidate...

    • can identify the marginal contribution of their research carry out his/her research with scholarly integrity
    • can communicate research in empirical asset pricing and actively participate in debates in the field in national and international scholarly forums

  • Teaching


    The class is lecture based, with student participation in class discussions as an expected component.

  • Required prerequisites

    Required prerequisites

    PhD level course in asset pricing theory, PhD level course in econometrics or time-series statistics.

  • Requirements for course approval

    Requirements for course approval

    There will be a substantial required homework assignment, which will be due by the end of the semester (usually sometime in November). I expect students to spend two weeks on finishing this assignment. Most people do not acquire a deep understanding of empirical issues without actually doing empirical work. Therefore you will be assigned exercises that require dealing with data and estimating models. You are free to use any software available to you to perform this empirical work. Matlab, Stata, and Eviews are recommended.


    Class participation is mandatory. You are expected to be prepared to discuss and answer questions related to the required readings.


    The homework will be handed out September 16th and is due in the morning of December 8th in class. We will then go through the homework in detail and discuss recent developments in empirical asset pricing such as models with financial frictions and intermediaries in the remainder of the class time on December 8th and 9th.

  • Assessment


    There will be a final exam at the end of the semester which counts for 55% of the grade. The problem set will count for 35% of the grade. Class participation will account for the remaining 10% of the grade.

  • Grading Scale

    Grading Scale

    Grading scale A - F.

  • Computer tools

    Computer tools

     The problem set requires knowledge of basic coding using MatLab or similar.

  • Semester


    Autumn 2016: Lectures September 14th, 15th and 16th and December 8th and 9th.


    Class Schedule:

    Onsdag 14.september 10-16: Karl Borch

    Torsdag 15.september 10-16: Aud D

    Fredag 16.september 10-16: Terje Hansen


    Torsdag 8.desember 0930-1530: Terje Hansen

    Fredag 9. desember 0930-1530: Terje Hansen

  • Literature




    I will distribute lecture notes in class. You are required to yourself download and, if you want, print copies of any journal articles that we will cover. References are given in the back of this document, and I will in class let you know which articles we will focus on for each class.


    We will read substantial parts of the following book:


    Cochrane, John, 2005, Asset Pricing: Revised Edition Princeton, NJ: Princeton University Press


    It is referred to as ( AP ) in the reading list.

    Other excellent reference books are the following:


    Campbell, John Y., Andrew W. Lo, and A. Craig MacKinlay, 1997, The Econometrics of Financial Markets, Princeton, NJ: Princeton University Press


    Duffie, Darrell, 2001, Dynamic Asset Pricing Theory, 3rd Edition, Princeton, NJ: Princeton University Press


    Singleton, Kenneth J., 2006, Empirical Dynamic Asset Pricing, Princeton, NJ: Princeton University Press


    Hamilton, James D., 1994, Time Series Analysis, Princeton, NJ: Princeton University Press


    You will need access to Matlab, Gauss or some other matrix programming language.


    The Reading List includes both classics that you should read at some point and newer material to give you an idea of how people are approaching the subject more recently.


    Tentative Reading List


    We may deviate from this reading list. I will let you know about any such deviations in class.



    1. The CAPM and an econometric review


    a. Methodology: CAPM, OLS, and early tests of the CAPM


    • Any source to review CAPM theory. In AP, it is Ch. 9, but this chapter depends on Chapters 4, 5, and 6 as well.
    • Time-series tests: Gibbons, Ross and Shanken (1989). AP Ch. 12.
    • Cross-sectional tests: AP pp. 434 - 452.
    • Other references: Shanken (1987), Shanken (1992), Black, Jensen, and Scholes (1972), Fama and MacBeth (1973)


    b. Landmark critique of the unconditional CAPM

    • Fama and French (1992)


    c. Methodology: review of asymptotics for OLS and robust standard errors


    • Any graduate-level econometrics textbook (e.g., Hamilton, referenced above).



    2. Multifactor models I: Methodology, linear K-factor models, and anomalies


    a. The Fama-French Model and critiques


    • Fama and French (1993)
    • AP Ch. 9
    • MacKinlay (1995)
    • Lo and MacKinlay (1990)
    • Berk (1995)
    • Daniel and Titman (1997)



    b. General linear factor models


    • AP Ch. 13


    c. Anomalies and establishing a new stylized fact


    • Momentum: Jegadeesh and Titman (1993), Asness, Moskowitz, and Pedersen (2009)
    • Liquidity: Pastor and Stambaugh (2003)
    • Idiosyncratic volatility: Ang, Hodrick, Xing, and Zhang (2006, 2009)
    • Social networks: Cohen, Frazzini, and Malloy (2008)
    • Inattention: Cohen and Frazzini (2008)


    d. Factor models and fund performance measurement

    • Background reading: Carhart (1997), Berk and Green (2004)
    • Mutual fund performance: Kosowski, Timmermann, Wermers, and White (2006)
    • Hedge fund performance: Fung, Hsieh, Ramadorai, and Naik (2008)



    3. Time-series properties of returns I: Predictability


    • AP Ch. 20.1
    • Shiller (1981)
    • Fama and French (1989)
    • Campbell and Shiller (1988)
    • Lettau and Ludvigsson (2001a)
    • Hodrick (1992)
    • Stambaugh (1999)
    • Boudoukh, Michaely, Richardson, and Roberts (2007)
    • Ang and Bekaert (2006)
    • Cochrane (2008)
    • Pastor and Stambaugh (2009)



    4. Beyond the unconditional CAPM


    a. Conditional linear factor models


    • AP Ch. 8.
    • Lettau and Ludvigsson (2001b)
    • Lewellen and Nagel (2006)
    • Nagel and Singleton (2011)
    • Other references: Jagannathan and Wang (1996), Ferson and Harvey (1999), Petkova and Zhang (2005)


    b. Value, growth, and duration


    • Campbell (1991)
    • Campbell and Mei (1993)
    • Dechow, Sloan, and Soliman (2004)
    • Campbell and Vuolteenaho (2004)
    • van Binsbergen, Brandt, and Koijen (2010)
    • Other references: Campbell (1993), Cohen, Polk, and Vuolteenaho (2003), Cohen, Polk, and Vuolteenaho (2006), Lettau and Wachter (2007)



    5. Methodology: GMM tests of models with an observable stochastic discount factor


    • Hansen and Singleton (1982)
    • AP Ch. 10, 11
    • Other references: Hansen, Heaton and Yaron (1996)


    Required reading (although you do not need to follow in detail all of the math in the Hansen papers, especially when nonnegativity is imposed). The Jagannathan and Wang paper was suggested reading earlier in the semester. Here it is included because it develops an estimation methodology for the HJ-distance.


    • Hansen and Jagannathan (1991)
    • Hansen and Jagannathan (1997)
    • AP The material on H-J bounds in Chapter 5, and Chapters 13 - 16 (they are short chapters)
    • Jagannathan and Wang (1996)
    • Hodrick and Zhang (2001)
    • Li, Xu, and Zhang (2010)

    We will not discuss this related paper. It works out the econometrics of the HJ-distance when the null is that the econometrician has the wrong stochastic discount factor.

    • Hansen, Heaton, and Luttmer (1995)



    6. Consumption-based asset pricing


    • The standard Consumption CAPM (CCAPM) and general background material: AP Ch. 21, Campbell (2003), Working (1960), Parker and Julliard (2005)
    • The conditional CCAPM (e.g., habit): Lettau and Ludvigsson (2001b)
    • Long-run risk: Bansal, Kiku and Yaron (2007)
    • Euler equation errors: Lettau and Ludvigson (2009)
    • Heterogeneous agents: Vissing-Jorgensen (2002), Mankiw and Zeldes (1991)
    • Heterogeneous goods: Yogo (2006), Piazzesi, Schneider, and Tuzel (2007), Lochstoer (2009)
    • Consumption disaster risk: Barro, Nakamura, Steinsson, and Ursua (2009)
    • Learning: Johannes, Lochstoer, and Mou (2010)
    • Other references: Mehra and Prescott (1985), Campbell and Cochrane (1999), Bansal and Yaron (2004), Rietz (1988), Barro (2009).



    10. The term structure


    a. Motivation and some facts:

    • AP, Chapter 19
    • Litterman and Scheinkman (1991)
    • Campbell and Shiller (1991)
    • Bekaert and Hodrick (2001)
    • Cochrane and Piazzesi (2006), Cieslak and Povala (2011)
    • Bekaert, Hodrick, and Marshall (2001)


    b. Formal modeling:

    A good background source on this topic include


    • Piazzesi (2003)


    We will discuss some features of the following papers


    • Dai and Singleton (2000)
    • Duffee (2002)
    • Ang and Piazzesi (2003)
    • Duffee (2010)




    11. Financial Frictions


    Some background theory: Bernanke and Gertler (1989; agency costs, imperfect contracts, and business cycle fluctuations), Shleifer and Vishny (1997; limits to arbitrage), Kyotaki and Moore (1997; borrowing constraint related to market value of collateral in business cycle model), Brunnermeier and Pedersen (2008; funding liquidity, margin constraints).


    Pro-cyclical leverage of financial intermediaries: Adrian and Shin (2010)

    Financial Crisis and Consumption: Muir (2016)

    Broker-Dealer leverage growth and the xsec of stock returns: Adrian, Etula, and Muir (2013)

    Betting on Beta: Frazzini and Pedersen (2013)

    Embedded leverage: Frazzini and Pedersen (2013)


    Limits to arbitrage and market segmentation: Evidence from commodity markets

    Some background: Sundaresan (1981), Fama and French (1986).

    • Facts and Fantasies: Gorton and Rouwenhorst (2006)
    • Speculator capital: Etula (2010), Tang and Xiong (2010), Mou (2010)
    • Producer hedging and commodity prices: Acharya, Lochstoer, and Ramadorai (2013)


ECTS Credits
Teaching language
English. All lectures and coursework (including the students own) are to be completed in English.

Course responsible

Professor Lars A. Lochstoer

Uris Hall 405B

Phone: +1 (212) 851-2119

Email: lars.lochstoer@anderson.ucla.edu