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  • All HBS Web  (2,965)
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    • Research  (2,199)
    • Events  (43)
    • Multimedia  (14)
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  • August 2018 (Revised September 2018)
  • Case

LendingClub (A): Data Analytic Thinking (Abridged)

By: Srikant M. Datar and Caitlin N. Bowler
LendingClub was founded in 2006 as an alternative, peer-to-peer lending model to connect individual borrowers to individual investor-lenders through an online platform. Since 2014 the company has worked with institutional investors at scale. While the company assigns... View Details
Keywords: Data Science; Data Analytics; Investing; Loans; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction; Business Model
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Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (A): Data Analytic Thinking (Abridged)." Harvard Business School Case 119-020, August 2018. (Revised September 2018.)
  • Article

Beacon and Warning: Sherman Kent, Scientific Hubris, and the CIA's Office of National Estimates

By: J. Peter Scoblic
Would-be forecasters have increasingly extolled the predictive potential of Big Data and artificial intelligence. This essay reviews the career of Sherman Kent, the Yale historian who directed the CIA’s Office of National Estimates from 1952 to 1967, with an eye toward... View Details
Keywords: National Security; Analytics and Data Science; Analysis; Forecasting and Prediction; History
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Scoblic, J. Peter. "Beacon and Warning: Sherman Kent, Scientific Hubris, and the CIA's Office of National Estimates." Texas National Security Review 1, no. 4 (August 2018).
  • 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
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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
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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.
  • Article

Why Do Pro Forma and Street Earnings Not Reflect Changes in GAAP? Evidence from SFAS 123R

By: Ian D. Gow, Mary E. Barth and Daniel Taylor
This study examines how key market participants—managers and analysts—responded to SFAS 123R's controversial requirement that firms recognize stock-based compensation expense. Despite mandated recognition of the expense, some firms' managers exclude it from pro forma... View Details
Keywords: Motivation and Incentives; Employee Stock Ownership Plan
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Gow, Ian D., Mary E. Barth, and Daniel Taylor. "Why Do Pro Forma and Street Earnings Not Reflect Changes in GAAP? Evidence from SFAS 123R." Review of Accounting Studies 17, no. 3 (September 2012): 526–562.
  • 2019
  • Article

Does Big Data Enhance Firm Innovation Competency? The Mediating Role of Data-driven Insights

By: Maryam Ghasemaghaei and Goran Calic
Grounded in gestalt insight learning theory and organizational learning theory, we collected data from 280 middle and top-level managers to investigate the impact of each big data characteristic (i.e., data volume, data velocity, data variety, and data veracity) on... View Details
Keywords: Analytics and Data Science; Innovation and Invention; Learning
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Ghasemaghaei, Maryam, and Goran Calic. "Does Big Data Enhance Firm Innovation Competency? The Mediating Role of Data-driven Insights." Journal of Business Research 104 (2019): 69–84.
  • 2009
  • Working Paper

Stock Price Fragility

By: Robin Greenwood and David Thesmar
We investigate the relationship between ownership structure of financial assets and non-fundamental risk. An asset is fragile if its owners collectively have to buy or sell. Such assets are susceptible to non-fundamental price movements. An asset can be fragile because... View Details
Keywords: Financial Liquidity; Stocks; Price; Market Transactions; Ownership; Risk and Uncertainty; United States
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Greenwood, Robin, and David Thesmar. "Stock Price Fragility." Harvard Business School Working Paper, No. 10-031, October 2009.
  • 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
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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.
  • 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
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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.)
  • 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
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Calvo, Richard, Vincent Pons, and Jesse M. Shapiro. "Pitfalls of Demographic Forecasts of U.S. Elections." NBER Working Paper Series, No. 33016, October 2024.
  • July 1986 (Revised August 1987)
  • Background Note

Note on Comparative Advantage

By: David B. Yoffie and John J. Coleman
Discusses David Ricardo's theory of comparative advantage and the refinement of his model developed by Eli Heckscher and Bertil Ohlin. Presents several criticisms of the Heckscher-Ohlin theory, including Wassily Leontief's empirical demonstration that the nature of... View Details
Keywords: Business Model; Forecasting and Prediction; Macroeconomics; Trade; Theory
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Yoffie, David B., and John J. Coleman. "Note on Comparative Advantage." Harvard Business School Background Note 387-023, July 1986. (Revised August 1987.)
  • February 2013
  • Case

Recorded Future: Analyzing Internet Ideas About What Comes Next

Recorded Future is a "big data" startup company that uses Internet data to make predictions about events, people, and entities. The company primarily serves government intelligence agencies, but has some private sector clients and is considering taking on more. The... View Details
Keywords: Big Data; Analytics; Internet; Analytics and Data Science; Internet and the Web; Entrepreneurship; Forecasting and Prediction; Business Startups; Information Technology Industry
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Davenport, Thomas H. "Recorded Future: Analyzing Internet Ideas About What Comes Next." Harvard Business School Case 613-083, February 2013.
  • 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
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Enke, Benjamin, Mattias Polborn, and Alex A Wu. "Values as Luxury Goods and Political Polarization." Working Paper, April 2022. (Revised April 2023.)
  • December 2009
  • Article

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 incentives... View Details
Keywords: Stocks; Stock Shares; Investment; Investment Return; Price; Theory; Valuation
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Baker, Malcolm, Robin Greenwood, and Jeffrey Wurgler. "Catering Through Nominal Share Prices." Journal of Finance 64, no. 6 (December 2009): 2559–2590. (Internet Appendix.)
  • 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
Keywords: Stocks; Stock Shares; Investment; Investment Return; Price; Theory; Valuation
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Baker, Malcolm, Robin Greenwood, and Jeffrey Wurgler. "Catering through Nominal Share Prices." NBER Working Paper Series, No. w13762, January 2008. (First Draft in 2007.)
  • May 2012
  • Article

Complicated Firms

By: Lauren Cohen and Dong Lou
We exploit a novel setting in which the same piece of information affects two sets of firms: one set of firms requires straightforward processing to update prices, while the other set requires more complicated analyses to incorporate the same piece of information into... View Details
Keywords: Investment Portfolio; Information; Price; Forecasting and Prediction; Complexity; Mathematical Methods
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Cohen, Lauren, and Dong Lou. "Complicated Firms." Journal of Financial Economics 104, no. 2 (May 2012). (Winner of Istanbul Stock Exchange 25th Anniversary Best Paper Competition. First Prize presented by Istanbul Stock Exchange. Winner of Center for Research in Security Prices Forum. Best Paper Prize presented by University of Chicago Booth School of Business. Winner of Paul Woolley Centre for the Study of Capital Market Dysfunctionality. Academic Grant presented by Paul Woolley Centre for the Study of Capital Market Dysfunctionality. Winner of Crowell Memorial Prize For the best paper on quantitative investing presented by PanAgora Asset Management, Inc.)
  • 09 Jun 2020
  • Working Paper Summaries

Aggregate and Firm-Level Stock Returns During Pandemics, in Real Time

Keywords: by Laura Alfaro, Anusha Chari, Andrew Greenland, and Peter K. Schott
  • 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
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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.)
  • June 2016
  • Article

Corporate Governance and Executive Compensation for Corporate Social Responsibility

By: Bryan Hong, Zhichuan (Frank) Li and Dylan B. Minor
We link the corporate governance literature in financial economics to the agency cost perspective of corporate social responsibility (CSR) to derive theoretical predictions about the relationship between corporate governance and the existence of executive compensation... View Details
Keywords: Corporate Social Responsibility; Incentives For CSR; Non-financial Performance Measures; Agency Costs; Board Independence; Institutional Holdings; Managerial Power; Motivation and Incentives; Corporate Social Responsibility and Impact; Executive Compensation; Corporate Governance
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Hong, Bryan, Zhichuan (Frank) Li, and Dylan B. Minor. "Corporate Governance and Executive Compensation for Corporate Social Responsibility." Journal of Business Ethics 136, no. 1 (June 2016): 199–213.
  • 07 Apr 2003
  • What Do You Think?

Should Global Business Initiatives Be Devalued?

recently, has been unthinkable: that global initiatives in many cases should be devalued, discounted, or postponed in relation to more predictable business investments "closer to home?" What do you think? View Details
Keywords: by James Heskett
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