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(2,833)
- News (448)
- Research (2,171)
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- Faculty Publications (1,383)
Show Results For
- All HBS Web
(2,833)
- News (448)
- Research (2,171)
- Events (39)
- Multimedia (14)
- Faculty Publications (1,383)
- 21 Oct 2015
- Research & Ideas
How to Predict if a New Business Idea is Any Good
other once unlikely, now successful startups (LinkedIn similarly got more than 20 rejections back in 2003) seem to beg: How do you tell a good idea from a bad one? “With startups, especially high-growth startups, it’s extremely hard to View Details
- March 2013
- Article
Misvaluing Innovation
By: Lauren Cohen, Karl Diether and Christopher Malloy
We demonstrate that a firm's ability to innovate is predictable, persistent, and relatively simple to compute, and yet the stock market ignores the implications of past successes when valuing future innovation. We show that two firms that invest the exact same in... View Details
Keywords: Innovation; Return Predictability; R＆D; Information; Forecasting and Prediction; Research and Development; Innovation and Invention
Cohen, Lauren, Karl Diether, and Christopher Malloy. "Misvaluing Innovation." Review of Financial Studies 26, no. 3 (March 2013): 635–666.
- 2023
- Working Paper
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
By: Daniel Yue, Paul Hamilton and Iavor Bojinov
Predictive model development is understudied despite its centrality in modern artificial
intelligence and machine learning business applications. Although prior discussions
highlight advances in methods (along the dimensions of data, computing power, and
algorithms)... View Details
Keywords: Analytics and Data Science
Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
Predictive model development is understudied despite its importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of... View Details
- May 2018
- Article
The Amount and Source of Millionaires' Wealth (Moderately) Predicts Their Happiness
By: Grant Edward Donnelly, Tianyi Zheng, Emily Haisley and Michael I. Norton
Two samples of more than 4,000 millionaires reveal two primary findings. First, only at high levels of wealth—in excess of $8 million (Study 1) and $10 million (Study 2)—are wealthier millionaires happier than millionaires with lower levels of wealth, though these... View Details
Donnelly, Grant Edward, Tianyi Zheng, Emily Haisley, and Michael I. Norton. "The Amount and Source of Millionaires' Wealth (Moderately) Predicts Their Happiness." Personality and Social Psychology Bulletin 44, no. 5 (May 2018): 684–699.
- 31 May 2023
- Research & Ideas
With Predictive Analytics, Companies Can Tap the Ultimate Opportunity: Customers’ Routines
If knowing what customers need is marketing gold, pinpointing exactly when they need it may just be platinum. Services that become part of a customer’s routine may deliver advantages beyond repeat business for a company, Harvard Business School Associate Professor Eva... View Details
- April 2024
- Article
A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification
By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson
Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),... View Details
Wang, Hsin-Hsiao Scott, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow, and Caleb Nelson. "A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification." Journal of Pediatric Urology 20, no. 2 (April 2024): 271–278.
- June 2023
- Case
Accounting for Loan Losses at JPMorgan Chase: Predicting Credit Costs
By: Jonas Heese, Jung Koo Kang and James Weber
The case examines the accounting for loan losses at a large bank, how a bank sets its Allowance for Loan and Lease Losses (ALLL) on its financial statements. ALLL, and the rules that set them, determine when banks would and would not extend loans, which significantly... View Details
Keywords: Accounting Standards; Accrual Accounting; Financial Statements; Financial Reporting; Banks and Banking; Financing and Loans; Banking Industry; United States
Heese, Jonas, Jung Koo Kang, and James Weber. "Accounting for Loan Losses at JPMorgan Chase: Predicting Credit Costs." Harvard Business School Case 123-042, June 2023.
- 1996
- Other Unpublished Work
Testing for Structural Change in the Predictability of Asset Returns
By: Luis M. Viceira
Viceira, Luis M. "Testing for Structural Change in the Predictability of Asset Returns." 1996.
- 10 Aug 2013 - 13 Aug 2013
- Conference Presentation
Stock Market Prediction via Social Media: The Importance of Competitors
By: Frank Nagle
5 Predictions for America's Small Businesses in the Biden Era
Karen Mills, the SBA Administrator under President Barack Obama, says the tea leaves suggest small business will be key to Biden’s economic agenda. View Details
- October 2023
- Teaching Note
Accounting for Loan Losses at JPMorgan Chase: Predicting Credit Costs
By: Jonas Heese and Jung Koo Kang
Teaching Note for HBS Case No. 123-042. View Details
- 15 Aug 2016
- Research & Ideas
Black Swans and Big Trends Can Ruin Anyone's Internet Prediction
investments are once again declining. Reasoning that today’s tech entrepreneurs and investors might value a history lesson, I’ve published Speed Trap as an ebook, which is downloadable for free in PDF format, and available in the iBooks Store for free and in the Kindle... View Details
- December 2023
- Supplement
Accounting for Loan Losses at JPMorgan Chase: Predicting Credit Costs
By: Jonas Heese and Jung Koo Kang
- Article
Interpretable Decision Sets: A Joint Framework for Description and Prediction
By: Himabindu Lakkaraju, Stephen H. Bach and Jure Leskovec
Lakkaraju, Himabindu, Stephen H. Bach, and Jure Leskovec. "Interpretable Decision Sets: A Joint Framework for Description and Prediction." Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 22nd (2016).
- November 2023
- Article
Knowledge About the Source of Emotion Predicts Emotion-Regulation Attempts, Strategies, and Perceived Emotion-Regulation Success
By: Yael Millgram, Matthew K. Nock, David D. Bailey and Amit Goldenberg
People’s ability to regulate emotions is crucial to healthy emotional functioning. One overlooked aspect in emotion-regulation research is that knowledge about the source of emotions can vary across situations and individuals, which could impact people’s ability to... View Details
Millgram, Yael, Matthew K. Nock, David D. Bailey, and Amit Goldenberg. "Knowledge About the Source of Emotion Predicts Emotion-Regulation Attempts, Strategies, and Perceived Emotion-Regulation Success." Psychological Science 34, no. 11 (November 2023): 1244–1255.
- 2023
- Chapter
Analyzing Human Decisions and Machine Predictions in Bail Decision Making
By: Jon Kleinberg, Himabindu Lakkaraju, Jure Leskovec, Jens Ludwig and Sendhil Mullainathan
BOOK ABSTRACT: Oriented toward the introductory student, The Inequality Reader is the essential textbook for today's undergraduate courses. The editors have assembled the most important classic and contemporary readings about how poverty and inequality are... View Details
Keywords: Equality and Inequality
Kleinberg, Jon, Himabindu Lakkaraju, Jure Leskovec, Jens Ludwig, and Sendhil Mullainathan. "Analyzing Human Decisions and Machine Predictions in Bail Decision Making." In The Inequality Reader: Contemporary and Foundational Readings in Race, Class, and Gender. 3rd edition, edited by David B. Grusky and Szonja Szelényi. Routledge, forthcoming.
- 9 May 2013 - 11 May 2013
- Conference Presentation
Stock Market Prediction via Social Media: The Importance of Competitors
By: Frank Nagle
- 31 Oct 2017
- News