Asset Pricing Workshop I

Learning outcomes:
Participants will be introduced to the research frontier in empirical asset pricing by reading and discussing recent research papers. The workshop requires previous knowledge of the classic literature in empirical asset pricing, including a solid understanding of factor models, time-series and cross-sectional regressions, and the Generalized Method of Moments. The workshop has two main parts. In the first part, we will discuss recent research in empirical asset pricing. The goal is to give students an overview of what the current outstanding questions are in the field. The second part of the workshop is centered on student presentations of their own (preliminary) research. Each student will present their own research, which then will be discussed by the students and the lecturer. The goal here is to give each student valuable feedback on both the presentation itself and on the research project in a friendly environment.
The workshop is aimed at dissertation-stage PhD students. Faculty participation is also welcome, including presentation (in the second part of the workshop) of own research to obtain feedback.

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 and 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 

The workshop is based on recent research papers and the main topics will include the cross-section and time-series of stock returns, financial frictions, intermediary asset pricing, as well as uses of machine learning and textual analysis in finance. In addition, the students’ own research papers in the general area of empirical asset pricing will be discussed.

The workshop is based on selected articles from top-tier finance and economics journals, as well as recent notable working papers in empirical asset pricing.

The workshop will consist of a combination of lectures and discussion where participation in discussions are important for all workshop participants.

Student presentations:
Each student that is ready to do so will present one of their working papers in the first day of class. The paper need not be polished, but there should be some concrete results and thought behind the economic 'story' (e.g., what is the marginal contribution? why is this important? what is the economic intuition for the results? etc). The students must prepare slides in PDF format (max 20 slides; printing to a pdf file ensures that tables, figures and equations look good regardless of platform) and bring a USB stick with their slides to the first day of class. All class participants are expected to comment constructively on the papers with the goal of improving the papers.

Computer requirements / Tools:
It is assumed that all interested students are facile with MatLab, Stata, etc.

Requirements for course approval:
Student participation in class, as well as a presentation of a research project of research idea.

A letter grade is given based on performance on the following three dimensions: (1) student presentation (50%), (2) class participation (50%).

Tentative reading list and class outline

Monday 21 August 2017

Time 10:15 - 16:00


Nagel, Stefan, 2013, Empirical Cross-Sectional Asset Pricing, Annual Review of Financial Economics, November issue.

Student presentations of research idea for the class project, each 15 mins, and class discussion.

Dynamic Risk-Return Trade-off

Lettau, M. and S. C. Ludvigson, 2010. Measuring and modeling variation in the riskreturn trade-off, Chapter 11 in Yacine Ait-Shalia and Lars Peter Hansen, eds., Handbook of Financial Econometrics: Volume 1 - Tools and Techniques, Elsevier: Amsterdam, The Netherlands.

Cochrane, John H., 2011, “Presidential Address: Discount Rates,” Journal of Finance 66, 1047–1108.

Lochstoer, Lars and Paul Tetlock, 2017, What Drives Anomaly Returns?, Columbia and UCLA working paper.

Kozak, S., Nagel, S., and S. Santosh, Interpreting Factor Models, 2016, forthcoming at the Journal of Finance.

Tuesday 22 August 2017

Time 10:15 -16:00

Machine Learning in Asset Pricing?

“Introduction to Statistical Learning”

“Elements of Statistical Learning”

Kozak, S., Nagel, S., and S. Santosh, 2017, Shrinking the Cross-Section, Chicago Booth working paper.

Textual Analysis in Finance

Introductory lecture material on textual analysis handed out in class.

Macskassy, S., Saar-Tsechansky, M., and P. Tetlock, 2008, More Than Words: Quantifying Language to Measure Firms’ Fundamentals, Journal of Finance 63, 1437-1467.

Tetlock, P., 2011, All the news that’s fit to reprint: do investors react to stale information?, Review of Financial Studies 24, 1481-1512.

Cohen, L., Malloy, C., and Q. Ngyun, 2017, Lazy Prices, Harvard working paper.

Wednesday 23 August 2017

Time 10:15 - 16:00

Conditional Asset Pricing

Boguth, Oliver, Murray Carlson, Adlai Fisher, Mikhail Simutin, 2011, Conditional risk and performance evaluation: Volatility timing, overconditioning, and new estimates of momentum alphas, Journal of Financial Economics 102, 363-389.

Cederburg, S. And Michael S. O’Doherty, 2016, Does it pay to bet against beta? On the conditional performance of the beta anomaly, Journal of Finance 71, 737-774.

Moreira, A., and T. Muir, 2017, Volatility-Managed Portfolios, Journal of Finance, forthcoming.

Tail Risk

Bollerslev, Tim, Viktor Todorov, and Lai Xu, 2015, Tail risk premia and return predictability, Journal of Financial Economics.

Jurek, Jakub W., and Eric Stafford, 2015, The cost of capital for alternative investments, Journal of Finance, October, pp 2185-2226.

Kelly, B., H. Lustig, and S. Van Nieuwerburgh, Too-Systemic-To-Fail: What Option Markets Imply about Sector-Wide Government Guarantees, American Economic Review, forthcoming.