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- October 2024
- Article
Canary Categories
By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that... View Details
- 2024
- Working Paper
Ponzi Funds
By: Philippe van der Beck, Jean-Philippe Bouchaud and Dario Villamaina
Many active funds hold concentrated portfolios. Flow-driven trading causes price pressure, which
pushes up the funds’ existing positions resulting in realized returns. We decompose fund returns
into a price pressure (self-inflated) and a fundamental component and... View Details
- 2024
- Working Paper
Finance Without Exotic Risk
By: Pedro Bordalo, Nicola Gennaioli, Rafael La Porta and Andrei Shleifer
We address the joint hypothesis problem in cross-sectional asset pricing by using measured analyst expectations of earnings growth. We construct a firm-level measure of Expectations Based Returns (EBRs) that uses analyst forecast errors and revisions and shuts down any... View Details
- June 2024
- Article
Going Digital: Implications for Firm Value and Performance
By: Wilbur Chen and Suraj Srinivasan
We examine firm value and performance implications of the growing trend of non-technology companies engaging in digital transformation. We measure digital activities in firms based on the disclosure of digital words in the business description section of 10-Ks. Digital... View Details
- 2024
- Working Paper
Does the Case for Private Equity Still Hold?
By: Nori Gerardo Lietz and Philipp Chvanov
Private Equity (“PE”) received a 10-fold increase in capital flows since the Great Financial Crisis (“GFC”) Investors sought higher nominal returns relative to those they could obtain in the public capital markets. This paper questions the fundamental assumptions... View Details
- April 2024
- Article
Decision Authority and the Returns to Algorithms
By: Hyunjin Kim, Edward L. Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca
We evaluate a pilot in an Inspections Department to explore the returns to a pair of algorithms that varied in their sophistication. We find that both algorithms provided substantial prediction gains, suggesting that even simple data may be helpful. However, these... View Details
- April 2024
- Article
Demand-and-Supply Imbalance Risk and Long-Term Swap Spreads
By: Samuel G. Hanson, Aytek Malkhozov and Gyuri Venter
We develop and test a model in which swap spreads are determined by end users' demand for
and constrained intermediaries’ supply of long-term interest rate swaps. Swap spreads reflect
compensation both for using scarce intermediary capital and for bearing convergence... View Details
- 2024
- Working Paper
Valuing Stocks With Earnings
By: Sebastian Hillenbrand and Odhrain McCarthy
We show that commonly used aggregate earnings are several times as volatile as stock prices
over the last three decades. Movements in the price-earnings ratio are thus entirely explained by
earnings growth and unrelated to future returns. As an alternative to the... View Details
- February 2024
- Teaching Note
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
Teaching Note for HBS Case No. 224-029. Levi Strauss & Co. (“Levi Strauss”) partnered with the IT services company Wipro to incorporate more sophisticated methods, such as machine learning, into their financial forecasting process starting in 2018. The decision to... View Details
- 2023
- Working Paper
Do Active Funds Do Better in What They Trade?
By: Marco Sammon and John J. Shim
We develop two new, simple measures to quantify active fund decisions at the individual position level. The intuition is to separate passive rebalancing induced by flows and position changes from active rebalancing decisions. We find that additive active rebalancing --... View Details
- 2023
- Working Paper
The Optimal Stock Valuation Ratio
By: Sebastian Hillenbrand and Odhrain McCarthy
Trailing price ratios, such as the price-dividend and the price-earnings ratio, scale prices by trailing cash flow measures. They theoretically contain expected returns, yet, their performance in predicting stock market returns is poor. This is because of an omitted... View Details
- 2023
- Working Paper
Interest-Rate Risk and Household Portfolios
By: Sylvain Catherine, Max Miller, James Paron and Natasha Sarin
How are households exposed to interest-rate risk? When rates fall, households face lower future expected returns but those holding long-term assets—disproportionately the wealthy and middle-aged—experience capital gains. We study the hedging demand for long-term assets... View Details
- September 2023 (Revised January 2024)
- Case
AB InBev: Brewing Up Forecasts during COVID-19
By: Mark Egan, C. Fritz Foley, Esel Cekin and Emilie Billaud
In July 2021, the CEO of AB InBev's European operations and his team strategized to position the company for success post-pandemic. As the world's largest beer company, boasting over 500 brands, revenue of $46 billion, and a workforce of 160,000 in 2020, AB InBev... View Details
Keywords: Beer; Forecasting; COVID-19; Decision; Forecasting and Prediction; Analytics and Data Science; Crisis Management; Decisions; Financing and Loans; Investment Return; Resource Allocation; Distribution; Production; Business Processes; Strategic Planning; Health Pandemics; Digital Transformation; Markets; Food and Beverage Industry; Belgium; Europe; Latin America; North and Central America
- Article
Expected Stock Returns Worldwide: A Log-Linear Present-Value Approach
By: Akash Chattopadhyay, Matthew R. Lyle and Charles C.Y. Wang
This study provides the first large-scale study of the performance of expected-return proxies (ERPs) internationally. Analyst-forecast-based ICCs are sparsely populated and not robustly associated with future returns. Earnings-model-forecast-based ICCs are... View Details
- March 2022
- Article
Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field
Identifying high-growth microentrepreneurs in low-income countries remains a challenge due to a scarcity of verifiable information. With a cash grant experiment in India we demonstrate that community knowledge can help target high-growth microentrepreneurs; while the... View Details
- 2024
- Working Paper
What Triggers National Stock Market Jumps?
By: Scott R. Baker, Nicholas Bloom, Steven J. Davis and Marco Sammon
We examine newspapers the day after major stock-market jumps to evaluate the proximate cause, geographic source, and clarity of these events from 1900 in the US, 1930 in the UK and 1980 in 12 other countries. We find four main results. First, the United States plays an... View Details
- January 2022
- Article
Rational Habit Formation: Experimental Evidence from Handwashing in India
By: Reshmaan Hussam, Atonu Rabbani, Giovanni Reggiani and Natalia Rigol
We test the predictions of the rational addiction model, reconceptualized as rational habit formation, in the context of handwashing in rural India. To track handwashing, we design soap dispensers with timed sensors. We test for rational habit formation by informing... View Details
- Article
Megastudies Improve the Impact of Applied Behavioural Science
By: Katherine L. Milkman, Dena Gromet, Hung Ho, Joseph S. Kay, Timothy W. Lee, Pepi Pandiloski, Yeji Park, Aneesh Rai, Max Bazerman, John Beshears, Lauri Bonacorsi, Colin Camerer, Edward Chang, Gretchen Chapman, Robert Cialdini, Hengchen Dai, Lauren Eskreis-Winkler, Ayelet Fishbach, James J. Gross, Samantha Horn, Alexa Hubbard, Steven J. Jones, Dean Karlan, Tim Kautz, Erika Kirgios, Joowon Klusowski, Ariella Kristal, Rahul Ladhania, Jens Ludwig, George Loewenstein, Barbara Mellers, Sendhil Mullainathan, Silvia Saccardo, Jann Spiess, Gaurav Suri, Joachim H. Talloen, Jamie Taxer, Yaacov Trope, Lyle Ungar, Kevin G. Volpp, Ashley V. Whillans, Jonathan Zinman and Angela L. Duckworth
Policy-makers are increasingly turning to behavioural science for insights about how to improve citizens’ decisions and outcomes. Typically, different scientists test different intervention ideas in different samples using different outcomes over different time... View Details
- October 2021
- Article
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Nicolas Padilla and Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details
- July–August 2021
- Article
Why You Aren't Getting More from Your Marketing AI
By: Eva Ascarza, Michael Ross and Bruce G.S. Hardie
Fewer than 40% of companies that invest in AI see gains from it, usually because of one or more of these errors: (1) They don’t ask the right question, and end up directing AI to solve the wrong problem. (2) They don’t recognize the differences between the value of... View Details