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(2,861)
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Show Results For
- All HBS Web
(2,861)
- News (468)
- Research (2,200)
- Events (43)
- Multimedia (14)
- Faculty Publications (1,410)
- 07 Jun 2019
- Working Paper Summaries
Reflexivity in Credit Markets
- 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
Cespedes, Frank V., John Deighton, Lisa Cox, and Olivia Hull. "DataXu: Selling Ad Tech." Harvard Business School Case 817-012, October 2016. (Revised April 2018.)
- 2008
- Working Paper
Catering through Nominal Share Prices
By: Malcolm Baker, Robin Greenwood and Jeffrey Wurgler
We propose and test a catering theory of nominal stock prices. The theory predicts that when investors place higher valuation on low-price firms, managers will maintain share prices at lower levels, and vice-versa. Using measures of time-varying catering... View Details
Baker, Malcolm, Robin Greenwood, and Jeffrey Wurgler. "Catering through Nominal Share Prices." NBER Working Paper Series, No. w13762, January 2008. (First Draft in 2007.)
- Article
Soul and Machine (Learning)
By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
Machine learning is bringing us self-driving cars, medical diagnoses, and language translation, but how can machine learning help marketers improve marketing decisions? Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to... View Details
Keywords: Machine Learning; Marketing Applications; Knowledge; Technological Innovation; Core Relationships; Marketing; Applications and Software
Proserpio, Davide, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu, and Hema Yoganarasimhan. "Soul and Machine (Learning)." Marketing Letters 31, no. 4 (December 2020): 393–404.
- Article
The Cross Section of Expected Holding Period Returns and Their Dynamics: A Present Value Approach
By: Matthew R. Lyle and Charles C.Y. Wang
We provide a tractable model of firm-level expected holding period returns using two firm fundamentals—book-to-market ratio and ROE—and study the cross-sectional properties of the model-implied expected returns. We find that 1) firm-level expected returns and expected... View Details
Keywords: Expected Returns; Discount Rates; Holding Period Returns; Fundamental Valuation; Present Value; Valuation; Investment Return
Lyle, Matthew R., and Charles C.Y. Wang. "The Cross Section of Expected Holding Period Returns and Their Dynamics: A Present Value Approach." Journal of Financial Economics 116, no. 3 (June 2015): 505–525.
- 13 Apr 2017
- News
Three men + software = l'Elysée?
- December 2012
- Article
Evidence on the Use of Unverifiable Estimates in Required Goodwill Impairment
By: Karthik Ramanna and Ross L. Watts
SFAS 142 requires managers to estimate the current fair value of goodwill to determine goodwill write-offs. In promulgating the standard, the FASB predicted managers will, on average, use the fair value estimates to convey private information on future cash flows. The... View Details
Keywords: Goodwill Impairment; Fair-value Accounting; FASB; SFAS 142; Fair Value Accounting; Standards; Cash Flow; Agency Theory; Motivation and Incentives; Forecasting and Prediction; Goodwill Accounting
Ramanna, Karthik, and Ross L. Watts. "Evidence on the Use of Unverifiable Estimates in Required Goodwill Impairment." Review of Accounting Studies 17, no. 4 (December 2012): 749–780.
- 31 Oct 2004
- What Do You Think?
Should the Wisdom of Crowds Influence Our Thinking About Leadership?
have been found to be better than a few experts at everything from estimating the true magnitude of things (as in guessing the number of jelly beans in a jar) to diagnosing causes of problems (as in determining that the O-ring seals were the primary cause of the... View Details
Keywords: by James Heskett
Siyu Zhang
Siyu Zhang is a second-year doctoral student at HBS. Zhang joined Harvard Business School in 2020 as a Research Associate and has been working on macroeconomic forecasting projects. Prior to joining HBS, he was a Data Scientist at John Hancock, where he utilized... View Details
- 2024
- Working Paper
Pitfalls of Demographic Forecasts of U.S. Elections
By: Richard Calvo, Vincent Pons and Jesse M. Shapiro
Many observers have forecast large partisan shifts in the US electorate based on demographic trends. Such forecasts are appealing because demographic trends are often predictable even over long horizons. We backtest demographic forecasts using data on US elections... View Details
Keywords: Mathematical Methods; Voting; Political Elections; Trends; Forecasting and Prediction; Demographics
Calvo, Richard, Vincent Pons, and Jesse M. Shapiro. "Pitfalls of Demographic Forecasts of U.S. Elections." NBER Working Paper Series, No. 33016, October 2024.
- October 2022 (Revised December 2022)
- Case
SMART: AI and Machine Learning for Wildlife Conservation
By: Brian Trelstad and Bonnie Yining Cao
Spatial Monitoring and Reporting Tool (SMART), a set of software and analytical tools designed for the purpose of wildlife conservation, had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching and contributing to wildlife... View Details
Keywords: Business and Government Relations; Emerging Markets; Technology Adoption; Strategy; Management; Ethics; Social Enterprise; AI and Machine Learning; Analytics and Data Science; Natural Environment; Technology Industry; Cambodia; United States; Africa
Trelstad, Brian, and Bonnie Yining Cao. "SMART: AI and Machine Learning for Wildlife Conservation." Harvard Business School Case 323-036, October 2022. (Revised December 2022.)
- Research Summary
The Role of Financial and Information Intermediaries in the Capital Markets
Hutton's research investigates the role of financial analysts and short sellers in the pricing of equity securities. Recently, Hutton examines (with Patricia Dechow and Richard Sloan) the role of sell-side analysts' earnings forecasts in the pricing of common equity... View Details
- 06 Mar 2017
- News
Harvard Reveals Blueprint for Avoiding Stock Crashes
- 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
Lorsch, Jay W. "The Future of Boards: Meeting the Governance Challenges of the 21st Century." European Financial Review (August–September 2012), 2–4.
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
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). These outliers often originate from covariate shift,... View Details
DosSantos DiSorbo, Matthew, and Kris Ferreira. "Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift." Working Paper, February 2024.
- 2010
- Working Paper
Decoding Inside Information
By: Lauren Cohen, Christopher Malloy and Lukasz Pomorski
Using a simple empirical strategy, we decode the information in insider trades. Exploiting the fact that insiders trade for a variety of reasons, we show that there is predictable, identifiable "routine" insider trading that is not informative for the future of firms.... View Details
Keywords: Forecasting and Prediction; Stocks; Financial Markets; Investment; Investment Return; Investment Portfolio; Market Transactions
Cohen, Lauren, Christopher Malloy, and Lukasz Pomorski. "Decoding Inside Information." NBER Working Paper Series, No. 16454, October 2010. (Winner of Institute for Quantitative Investment Research (INQUIRE) Grant presented by Institute for Quantitative Investment Research. Winner of Chicago Quantitative Alliance Academic Paper Competition. First Prize presented by Chicago Quantitative Alliance.)
- 2022
- Working Paper
Values as Luxury Goods and Political Polarization
By: Benjamin Enke, Mattias Polborn and Alex A Wu
Motivated by novel survey evidence, this paper develops a theory of political
behavior in which values are a luxury good: the relative weight voters place
on values rather than material considerations increases in income. The model
predicts (i) voters who are... View Details
Keywords: Political Polarization; Government and Politics; Moral Sensibility; Luxury; Values and Beliefs; Voting
Enke, Benjamin, Mattias Polborn, and Alex A Wu. "Values as Luxury Goods and Political Polarization." Working Paper, April 2022. (Revised April 2023.)