Publications

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

Keywords: Investment Return; Financial Markets; Behavioral Finance; Risk and Uncertainty

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2009
Article

Compelled to Help: Effects of Direct and Indirect Exchange on Perceived Obligation in Professional Networks

By: Roy Y.J. Chua, Billian Sullivan and Michael W. Morris

This research examines felt obligation to help others in employees' and managers' professional networks using a social exchange perspective. We hypothesize that obligation toward others would follow the norms of both direct and indirect reciprocity. Direct reciprocity... View Details

Keywords: Perspective; Conflict of Interests; Research; Surveys; Networks; Forecasting and Prediction; Social Issues

May 2006
Case

Nokia in 2003

By: Paul M. Healy

Examines the challenges facing a money manager who owns stock in Nokia, the leading wireless handset provider. Two analysts covering the stock make very different predictions about the economies of the industry, Nokia's future performance, and stock recommendations.... View Details

Keywords: Financial Reporting; Forecasting and Prediction; Performance Effectiveness; Performance Evaluation; Problems and Challenges; Electronics Industry

Educators

06 Feb 2019
News

How Investment Made Singapore an Innovation Hub

18 Nov 2015
News

The internet of things will bring makers closer to customers

03 Jan 2014
News

Book Review: 'Fortune Tellers' by Walter Friedman

30 Apr 2020
News

A Harvard Professor Calling for Us to ‘Reimagine Capitalism’ Says COVID-19 Has Revealed 3 Fault Lines in Our Economy

October–December 2022
Article

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius

Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details

Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction

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Ashley Whillans is the Volpert Family Associate Professor of Business Administration at the Harvard Business School, where she teaches the Motivation and Incentives course to MBA students. Professor Whillans earned her PhD in Social Psychology from the University of... View Details

Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers

1. Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). How can humans and algorithms work together to... View Details

October 2000
Article

The Equity Share in New Issues and Aggregate Stock Returns

By: Malcolm Baker and Jeffrey Wurgler

The share of equity issues in total new equity and debt issues is a strong predictor of U.S. stock market returns between 1928 and 1997. In particular, firms issue more equity than debt just before periods of low market returns. The equity share in new issues has... View Details

Keywords: Equity; Borrowing and Debt; Stocks; Markets; Debt Securities; Forecasting and Prediction; Accounting Industry; United States

08 Dec 2010
Working Paper Summaries

Decoding Inside Information

Keywords: by Lauren Cohen, Christopher Malloy & Lukasz Pomorski; Financial Services

07 Jun 2019
Working Paper Summaries

Reflexivity in Credit Markets

Keywords: by Robin Greenwood, Samuel G. Hanson, and Lawrence J. Jin

October 2016 (Revised April 2018)
Case

DataXu: Selling Ad Tech

By: Frank V. Cespedes, John Deighton, Lisa Cox and Olivia Hull

DataXu served marketers by buying digital advertising for brands using its demand-side platform. It sought a way to build a more predictable revenue stream in the very transactional media marketplace, and hoped that two new marketing analytics products would give it a... View Details

Keywords: Sales Management; Pricing; Programmatic Ad Buying; ＂Marketing Analytics＂; Advertising Technology; Sales; Digital Marketing; Marketing Strategy; Advertising Campaigns; Product Launch; Product Positioning; Media; Technology Industry; Advertising Industry; Boston; Massachusetts

Educators

Purchase

06 Mar 2017
News

Harvard Reveals Blueprint for Avoiding Stock Crashes

January–February 2023
Article

Forecasting COVID-19 and Analyzing the Effect of Government Interventions

By: Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis and Dimitris Bertsimas

We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more... View Details

Keywords: COVID-19 Pandemic; Epidemics; Analytics and Data Science; Health Pandemics; AI and Machine Learning; Forecasting and Prediction

December 2023
Article

Save More Today or Tomorrow: The Role of Urgency in Precommitment Design

By: Joseph Reiff, Hengchen Dai, John Beshears, Katherine L. Milkman and Shlomo Benartzi

To encourage farsighted behaviors, past research suggests that marketers may be wise to invite consumers to pre-commit to adopt them “later.” However, the authors propose that people will draw different inferences from different types of pre-commitment offers, and that... View Details

Keywords: Consumer Behavior; Decision Choices and Conditions

Research Summary

Implications of Limits of Arbitrage (with James Choi)

In this project we investigate the relationship between limits to arbitrage facing mutual fund managers and asset pricing anomalies. We measure changes in the limits to arbitrage by computing the average of slopes on current and past returns in quarterly... View Details

August–September 2012
Article

The Future of Boards: Meeting the Governance Challenges of the 21st Century

By: Jay W. Lorsch

Predicting the challenges boards will face in the years ahead requires an understanding of how they and the governance they have provided has evolved in past years, as well as the challenges they face in the years ahead. Since I have been serving on and doing research... View Details

Keywords: Boards Of Directors; Corporate Governance; Governance; Succession; Compensation; Governing and Advisory Boards