Exam Preparation

Exam Preparation#

This page is the running outline of what the exam covers. It is the single source of truth for scope: if a page, notebook, or paper is listed here, it is fair game.

Format#

The exam is in-person, closed-book, closed-notes, multiple choice, answered on a bubble sheet. Each question has four options, (A) through (D), and one or more options may be correct. Most questions have more than one correct option, and in some every option is correct. You are not told how many to select. A question earns its point only if every bubble is right: all correct options filled in and all incorrect options left blank. There is no partial credit.

Questions test three things in roughly equal measure:

  • The tools. What each tool in the pipeline is for, how it is invoked, and what its configuration means. Expect short code blocks (a dodo.py, a SQL query, a workflow YAML file, a cron line, an sbatch script) followed by “what happens” or “what is wrong here”.

  • The data. What each dataset is, who provides it, how we access it, its key identifiers and fields, and the quirks the notes call out.

  • The papers. What each replicated paper did, how the replication constructs it, and what it finds.

The Exam#

The exam is held in class in week 9, on Tuesday, December 1, in the first 75 minutes, and covers the material through week 8: all lecture notes, in-class discussions, the notebooks linked from the weekly chapters, and Homework 1 through 5. That includes Apache Airflow (week 7) and GitHub Actions (week 8). The room is posted on Canvas. There is no separate final exam.

Practice Questions#

A set of practice questions in the same format, with the answer key, is handed out ahead of the exam. It is not graded. Work it under exam conditions and grade yourself; the answer key explains why each option is right or wrong.

Online Notes#

We do not cover every page of the online notes in class. All material in the course notes is fair game, including pages not explicitly discussed in class. You are responsible for reading the full notes on your own. Each week’s chapter opens with a table of contents listing the pages for that week; those pages and the notebooks they link to are the scope.

Homework Assignments#

Each homework page and the notebooks it links to (“HW guides”) may appear on the exam. Questions about the homework ask what the pipeline does and why, not for the numerical results.

Papers#

The following papers and methods are covered in the notes and may appear on the exam. More are added here as the quarter progresses.

  • Markowitz, H. (1952). Portfolio Selection. Journal of Finance, 7(1), 77–91.

  • Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance, 19(3), 425–442. The CAPM, as the framing for the CRSP market portfolio and the S&P 500 reconstruction.

  • Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3–56. Including the investment (asset growth) sort from Fama and French (2015), A five-factor asset pricing model, Journal of Financial Economics, 116(1), 1–22.

  • Gürkaynak, R. S., Sack, B., & Wright, J. H. (2007). The U.S. Treasury yield curve: 1961 to the present. Journal of Monetary Economics, 54(8), 2291–2304. (Federal Reserve Board working paper 2006-28.)

  • The CME FedWatch methodology: implying FOMC meeting-outcome probabilities from 30-Day Federal Funds futures.

  • Dick-Nielsen, J. (2009, 2014). Liquidity biases in TRACE, and How to clean Enhanced TRACE data. As implemented in the Clean TRACE walkthrough.

  • Martin, I., & Shi, R. (2025). Forecasting crashes with a smile. Working paper. Recovering the risk-neutral density from the volatility smile by Breeden-Litzenberger, and the crash-probability bounds.

  • Easley, D., López de Prado, M. M., & O’Hara, M. (2012). Flow toxicity and liquidity in a high-frequency world. Review of Financial Studies, 25(5), 1457–1493. Order book reconstruction, bulk volume classification, and VPIN in volume time.

  • Holden, C. W., & Jacobsen, S. (2014). Liquidity measurement problems in fast, competitive markets: Expensive and cheap solutions. Journal of Finance, 69(4), 1747–1785. Computing the NBBO and standard liquidity measures from TAQ, and why the choice between Daily and Monthly TAQ changes the answer.

  • Goyal, A., Welch, I., & Zafirov, A. (2024). A comprehensive 2022 look at the empirical performance of equity premium prediction. Review of Financial Studies, 37(11), 3490–3557. The predictors of the class report, the historical-mean benchmark, and why a forecast at date t may use only what was known at t.

  • Bernanke, B. S., & Kuttner, K. N. (2005). What explains the stock market’s reaction to Federal Reserve policy? Journal of Finance, 60(3), 1221–1257. Measuring the policy surprise from the fed funds futures price change on the announcement day.

Additional papers are posted here as the course progresses.

Contents