Filter Results:
(228)
Show Results For
- All HBS Web (228)
- Faculty Publications (106)
Show Results For
- All HBS Web (228)
- Faculty Publications (106)
- Article
Bringing Probability Judgments into Policy Debates via Forecasting Tournaments
By: Philip E. Tetlock, Barbara A. Mellers and J. Peter Scoblic
Political debates often suffer from vague-verbiage predictions that make it difficult to assess accuracy and improve policy. A tournament sponsored by the U.S. intelligence community revealed ways in which forecasters can better use probability estimates to make... View Details
Keywords: Tournaments; Politics; Depolarization; Knowledge Creation; Forecasting and Prediction; Government and Politics
Tetlock, Philip E., Barbara A. Mellers, and J. Peter Scoblic. "Bringing Probability Judgments into Policy Debates via Forecasting Tournaments." Science 355, no. 6324 (February 3, 2017): 481–483.
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
Keywords: Economics Of AI; Machine Learning; Non-stationarity; Perishability; Value Depreciation; Analytics and Data Science; Value
Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
- September 2018 (Revised December 2019)
- Case
Zebra Medical Vision
By: Shane Greenstein and Sarah Gulick
An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making... View Details
Keywords: Radiology; Machine Learning; X-ray; CT Scan; Medical Technology; Probability; FDA 510(k); Diagnosis; Business Startups; Health Care and Treatment; Information Technology; Applications and Software; Competitive Strategy; Product Development; Commercialization; Decision Choices and Conditions; Health Industry; Medical Devices and Supplies Industry; Technology Industry; Israel
Greenstein, Shane, and Sarah Gulick. "Zebra Medical Vision." Harvard Business School Case 619-014, September 2018. (Revised December 2019.)
- Research Summary
Sell-Side Analysts and Corporate Spinoffs
This study investigates the information content and accuracy of analyst reports written about companies that are about to undertake equity spinoffs. This research is among the first to provide a detailed look at the extent to which analysts evaluate upcoming... View Details
- 2014
- Working Paper
Corporate Financial Policies in Misvalued Credit Markets
By: Jarrad Harford, Marc Martos-Vila and Matthew Rhodes-Kropf
We theoretically and empirically investigate the repercussions of credit market misvaluation for a firm's borrowing and investment decisions. Using an ex-post measure of the accuracy of credit ratings to capture debt market misvaluation, we find evidence that firms... View Details
Harford, Jarrad, Marc Martos-Vila, and Matthew Rhodes-Kropf. "Corporate Financial Policies in Misvalued Credit Markets." Harvard Business School Working Paper, No. 14-097, April 2014.
- Forthcoming
- Article
FinTech Lending and Cashless Payments
By: Pulak Ghosh, Boris Vallée and Yao Zeng
Borrower's use of cashless payments both improves their access to capital from FinTech lenders and predicts a lower probability of default. These relationships are stronger for cashless technologies providing more precise information, and for outflows. Cashless payment... View Details
- July 1999
- Article
Analysts' Forecast Accuracy: Do Ability and Portfolio Complexity Matter
By: Michael B. Clement
Prior studies have identified systematic and time persistent differences in analysts’ earnings forecast accuracy, but have not explained why the differences exist. Using the I/B/E/S Detail History database, this study finds that forecast accuracy is positively... View Details
Clement, Michael B. "Analysts' Forecast Accuracy: Do Ability and Portfolio Complexity Matter." Journal of Accounting & Economics 27, no. 3 (July 1999): 285–303.
- February 2011
- Article
Understanding Analysts’ Use and Under-use of Stock Returns and Other Analysts’ Forecasts when Forecasting Earnings
By: Michael B. Clement, Jeffrey Hales and Yanfeng Xue
We investigate analysts' use of stock returns and other analysts' forecast revisions in revising their own forecasts after an earnings announcement. We find that analysts respond more strongly to these signals when the signals are more informative about future earnings... View Details
Keywords: Learning; Forecasting and Prediction; Performance Evaluation; Knowledge Use and Leverage; Financial Services Industry
Clement, Michael B., Jeffrey Hales, and Yanfeng Xue. "Understanding Analysts’ Use and Under-use of Stock Returns and Other Analysts’ Forecasts when Forecasting Earnings." Journal of Accounting & Economics 51, nos. 1-2 (February 2011): 279–299.
- 2011
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details
- Research Summary
Does the Adoption of Rolling Forecasts Improve Planning?
This field study investigates the consequences of adopting rolling forecasts on organizational planning. Using quarterly product-line forecasted and realized sales data from several business units of a multinational biotechnology supplier, I find that subsequent to the... View Details
- January 2020
- Article
The Job Rating Game: Revolving Doors and Analyst Incentives
By: Elisabeth Kempf
Investment banks frequently hire analysts from rating agencies. While many argue that this "revolving door" creates captured analysts, it can also create incentives to improve accuracy. To study this issue, I construct an original dataset, linking analysts to their... View Details
Keywords: Credit Rating Agencies; Investment Banking; Recruitment; Performance Evaluation; Financial Services Industry
Kempf, Elisabeth. "The Job Rating Game: Revolving Doors and Analyst Incentives." Journal of Financial Economics 135, no. 1 (January 2020): 41–67.
- April 12, 2022
- Article
Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the United States
By: Estee Y. Cramer, Evan L. Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Michael Lingzhi Li and et al.
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models... View Details
Keywords: COVID-19; Forecasting and Prediction; Health Pandemics; Mathematical Methods; Partners and Partnerships
Cramer, Estee Y., Evan L. Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Michael Lingzhi Li, and et al. "Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the United States." e2113561119. Proceedings of the National Academy of Sciences 119, no. 15 (April 12, 2022). (See full author list here.)
- 2015
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details
Speakman, Skyler, Edward McFowland III, and Daniel B. Neill. "Scalable Detection of Anomalous Patterns With Connectivity Constraints." Journal of Computational and Graphical Statistics 24, no. 4 (2015): 1014–1033.
- 1998
- Article
Alternative Models of Uncertain Commodity Prices for Use with Modern Asset Pricing Methods
By: Malcolm Baker, E. S. Mayfield and John Parsons
This paper provides an introduction to alternative models of uncertain commodity prices. A model of commodity price movements is the engine around which any valuation methodology for commodity production projects is built, whether discounted cash flow (DCF) models or... View Details
Keywords: Asset Pricing; Goods and Commodities; Price; Risk and Uncertainty; Valuation; Production; Projects; Cash Flow
Baker, Malcolm, E. S. Mayfield, and John Parsons. "Alternative Models of Uncertain Commodity Prices for Use with Modern Asset Pricing Methods." Energy Journal 19, no. 1 (1998): 115–148.
- March 2021
- Case
VideaHealth: Building the AI Factory
By: Karim R. Lakhani and Amy Klopfenstein
Florian Hillen, co-founder and CEO of VideaHealth, a startup that used artificial intelligence (AI) to detect dental conditions on x-rays, spent the early years of his company laying the groundwork for an AI factory. A process for quickly building and iterating on new... View Details
Keywords: Artificial Intelligence; Innovation and Invention; Disruptive Innovation; Technological Innovation; Information Technology; Applications and Software; Technology Adoption; Digital Platforms; Entrepreneurship; AI and Machine Learning; Technology Industry; Medical Devices and Supplies Industry; North and Central America; United States; Massachusetts; Cambridge
Lakhani, Karim R., and Amy Klopfenstein. "VideaHealth: Building the AI Factory." Harvard Business School Case 621-021, March 2021.
- 2019
- Working Paper
The Wisdom of Crowds in Operations: Forecasting Using Prediction Markets
By: Achal Bassamboo, Ruomeng Cui and Antonio Moreno
Prediction is an important activity in various business processes, but it becomes difficult when historical information is not available, such as forecasting demand of a new product. One approach that can be applied in such situations is to crowdsource opinions from... View Details
Keywords: Wisdom Of Crowds; Demand Forecasting; Price Forecasting; Forecasting and Prediction; Social and Collaborative Networks; Size; Performance
Bassamboo, Achal, Ruomeng Cui, and Antonio Moreno. "The Wisdom of Crowds in Operations: Forecasting Using Prediction Markets." Working Paper, 2019.
- December 2021
- Article
Entrepreneurial Learning and Strategic Foresight
By: Aticus Peterson and Andy Wu
We study how learning by experience across projects affects an entrepreneur's strategic foresight. In a quantitative study of 314 entrepreneurs across 722 crowdfunded projects supplemented with a program of qualitative interviews, we counterintuitively find that... View Details
Keywords: Crowdfunding; Experience; Prediction; Timeline; Complexity; Entrepreneurship; Learning; Experience and Expertise; Forecasting and Prediction
Peterson, Aticus, and Andy Wu. "Entrepreneurial Learning and Strategic Foresight." Art. 1. Strategic Management Journal 42, no. 13 (December 2021): 2357–2388. (Lead article.)
- 2021
- Working Paper
Entrepreneurial Learning and Strategic Foresight
By: Aticus Peterson and Andy Wu
We study how learning by experience across projects affects an entrepreneur's strategic foresight. In a quantitative study of 314 entrepreneurs across 722 crowdfunded projects supplemented with a program of qualitative interviews, we counterintuitively find that... View Details
Keywords: Experience; Interdependency; Strategic Foresight; Crowdfunding; Timeline; Delay; Forecasting; Entrepreneurship; Learning; Complexity; Forecasting and Prediction; Product Development; Planning
Peterson, Aticus, and Andy Wu. "Entrepreneurial Learning and Strategic Foresight." Harvard Business School Working Paper, No. 21-123, January 2021. (Revised May 2021.)
- 2020
- Article
Fast Exact Matrix Completion: A Unified Optimization Framework for Matrix Completion
By: Dimitris Bertsimas and Michael Lingzhi Li
We formulate the problem of matrix completion with and without side information as a non-convex optimization problem. We design fastImpute based on non-convex gradient descent and show it converges to a global minimum that is guaranteed to recover closely the... View Details
Keywords: Mathematical Methods
Bertsimas, Dimitris, and Michael Lingzhi Li. "Fast Exact Matrix Completion: A Unified Optimization Framework for Matrix Completion." Journal of Machine Learning Research 21, no. 1 (2020).