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      • Faculty Publications  (360)

      Forecasting And Prediction Remove Forecasting And Prediction →

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      Forecasting & Prediction: Articles, Research, & Case Studies on Forecasting & Prediction– HBS Working Knowledge
      Skip to Main Content Cold Call A podcast featuring faculty discussing cases they've written and the lessons they impart. Subscribe on iTunes 29 Sep...
      The Wisdom of Crowds in Operations: Forecasting Using Prediction Markets
      → Search All HBS Web
      • February 2021
      • Tutorial

      Assessing Prediction Accuracy of Machine Learning Models

      By: Michael Toffel and Natalie Epstein
      This video describes how to assess the accuracy of machine learning prediction models, primarily in the context of machine learning models that predict binary outcomes, such as logistic regression, random forest, or nearest neighbor models. After introducing and...  View Details
      Keywords: Machine Learning; Statistics; Experiments; Forecasting and Prediction; Performance Evaluation
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      Toffel, Michael, and Natalie Epstein. Assessing Prediction Accuracy of Machine Learning Models. Harvard Business School Tutorial 621-706, February 2021.
      • January–February 2021
      • Article

      Cross‐firm Return Predictability and Accounting Quality

      By: Wen Chen, Mozaffar Khan, Leonid Kogan and George Serafeim
      We test the hypothesis that if poor accounting quality (AQ) is associated with poor investor understanding of firms’ revenue and cost structures, then poor AQ stocks likely respond more slowly than good AQ stocks to new non‐idiosyncratic information that affects both...  View Details
      Keywords: Accounting Quality; Earnings Quality; Stock Returns; Investment Strategy; Accounting; Business Earnings; Quality; Investment Return; Investment; Strategy
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      Chen, Wen, Mozaffar Khan, Leonid Kogan, and George Serafeim. "Cross‐firm Return Predictability and Accounting Quality." Journal of Business Finance & Accounting 48, nos. 1-2 (January–February 2021): 70–101.
      • January 2021
      • Case

      Aster DM Healthcare: Budgeting for a Crisis

      By: V.G. Narayanan and Amy Klopfenstein
      In April 2020, Alisha Moopen, Deputy Managing Director of Aster DM Healthcare, a network of clinics, hospitals, and pharmacies in the Middle East and India, must create her company’s budget for the 2021 fiscal year in light of the onset of Covid-19. The pandemic had...  View Details
      Keywords: Decision Making; Decisions; Forecasting and Prediction; Judgments; Decision Choices and Conditions; Cost vs Benefits; Budgets and Budgeting; Health Pandemics; Health Industry; Asia; India; United Arab Emirates; Dubai
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      Narayanan, V.G., and Amy Klopfenstein. "Aster DM Healthcare: Budgeting for a Crisis." Harvard Business School Case 121-001, January 2021.
      • January 2021
      • Supplement

      Aster DM Healthcare: Budget Exercise

      By: V.G. Narayanan and Amy Klopfenstein
      In April 2020, Alisha Moopen, Deputy Managing Director of Aster DM Healthcare, a network of clinics, hospitals, and pharmacies in the Middle East and India, must create her company’s budget for the 2021 fiscal year in light of the onset of Covid-19. The pandemic had...  View Details
      Keywords: Decision Making; Decisions; Forecasting and Prediction; Judgments; Decision Choices and Conditions; Cost vs Benefits; Finance; Borrowing and Debt; Financial Institutions; Banks and Banking; Financial Condition; Financial Liquidity; Accounting; Budgets and Budgeting; Management; Crisis Management; Health Pandemics; Health Industry; Asia; India; United Arab Emirates; Dubai
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      Narayanan, V.G., and Amy Klopfenstein. "Aster DM Healthcare: Budget Exercise." Harvard Business School Spreadsheet Supplement 121-025, January 2021.
      • January 2021 (Revised March 2021)
      • Case

      THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

      By: Jill Avery, Ayelet Israeli and Emma von Maur
      THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on...  View Details
      Keywords: Data; Data Analytics; Artificial Intelligence; Ai; Ai Algorithms; Ai Creativity; Fashion; Retail; Retail Analytics; Digital Marketing; E-commerce; E-commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; "marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Data and Data Sets; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Online Advertising; Online Technology; Mobile Technology; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
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      Avery, Jill, Ayelet Israeli, and Emma von Maur. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Case 521-070, January 2021. (Revised March 2021.)
      • January 2021
      • Case

      The FIRE Savings Calculator

      By: Michael Parzen and Paul J. Hamilton
      This case follows Carol Muñoz, a member of the Financial Independence, Retire Early (FIRE) lifestyle movement. At the age of 45, Carol is considering retiring and living off the $1 million she has accumulated. Using Monte Carlo simulation, Carol forecasts the...  View Details
      Keywords: Analysis; Forecasting and Prediction; Financial Strategy; Investment Portfolio; Investment Return; Personal Finance; Saving; Risk and Uncertainty; Diversification; Theory; Financial Services Industry
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      Parzen, Michael, and Paul J. Hamilton. "The FIRE Savings Calculator." Harvard Business School Case 621-087, January 2021.
      • 2021
      • Working Paper

      Real Credit Cycles

      By: Pedro Bordalo, Nicola Gennaioli, Andrei Shleifer and Stephen J. Terry
      We incorporate diagnostic expectations, a psychologically founded model of overreaction to news, into a workhorse business cycle model with heterogeneous firms and risky debt. A realistic degree of diagnosticity, estimated from the forecast errors of managers of U.S....  View Details
      Keywords: Econometric Models; Business Cycles; Credit
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      Bordalo, Pedro, Nicola Gennaioli, Andrei Shleifer, and Stephen J. Terry. "Real Credit Cycles." NBER Working Paper Series, No. 28416, January 2021.
      • January 2021
      • Article

      Using Models to Persuade

      By: Joshua Schwartzstein and Adi Sunderam
      We present a framework where "model persuaders" influence receivers’ beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers’ prior beliefs. Model...  View Details
      Keywords: Model Persuasion; Data and Data Sets; Forecasting and Prediction; Mathematical Methods; Framework
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      Schwartzstein, Joshua, and Adi Sunderam. "Using Models to Persuade." American Economic Review 111, no. 1 (January 2021): 276–323.
      • December 2020
      • Teaching Note

      Forecasting ClimaCell

      By: Joshua Lev Krieger, Christopher Stanton and James Barnett
      A weather technology startup, ClimaCell considers the R&D trade-offs and financing implications of pursuing a proposed contract with a major automobile maker, rather than continuing its focus on building a scalable, all-purpose weather prediction engine.  View Details
      Keywords: Weather; Forecasting and Prediction; Business Startups; Research and Development; Finance; Cost vs Benefits; Decision Making; Strategy; United States; Israel; Massachusetts; Colorado
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      Krieger, Joshua Lev, Christopher Stanton, and James Barnett. "Forecasting ClimaCell." Harvard Business School Teaching Note 821-008, December 2020.
      • November 2020
      • Case

      Axis My India

      By: Ananth Raman, Ann Winslow and Kairavi Dey
      "Pradeep Gupta founded Axis My India (AMI) as a printing and publishing company in 1998. In 2013, AMI expanded into consumer research and election forecasting. Although a relatively unknown entity, AMI predicted several election results accurately. Gupta describes...  View Details
      Keywords: Market Research; Operations; Management; Infrastructure; Logistics; Service Operations; Political Elections; Forecasting and Prediction; Asia; India
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      Raman, Ananth, Ann Winslow, and Kairavi Dey. "Axis My India." Harvard Business School Case 621-075, November 2020.
      • August 2020 (Revised September 2020)
      • Technical Note

      Assessing Prediction Accuracy of Machine Learning Models

      By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne
      The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools...  View Details
      Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Data and Data Sets; Analysis; Mathematical Methods
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      Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
      • 2021
      • Working Paper

      Predictable Financial Crises

      By: Robin Greenwood, Samuel G. Hanson, Andrei Shleifer and Jakob Ahm Sørensen
      Using historical data on post-war financial crises around the world, we show that crises are substantially predictable. The combination of rapid credit and asset price growth over the prior three years, whether in the nonfinancial business or the household sector, is...  View Details
      Keywords: Financial Crisis; Forecasting and Prediction; Mathematical Methods
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      Greenwood, Robin, Samuel G. Hanson, Andrei Shleifer, and Jakob Ahm Sørensen. "Predictable Financial Crises." NBER Working Paper Series, No. 27396, June 2020. (Revised March 2021. Harvard Business School Working Paper, No. 20-130, June 2020)
      • 2020
      • Working Paper

      Business Reopening Decisions and Demand Forecasts During the COVID-19 Pandemic

      By: Dylan Balla-Elliott, Zoë B. Cullen, Edward L. Glaeser, Michael Luca and Christopher Stanton
      How quickly will American businesses reopen after COVID-19 lockdowns end? We use a nationwide survey of small businesses to measure firms’ expectations about their re-opening and future demand. A plurality of firms in our sample expect to reopen within days of the end...  View Details
      Keywords: Covid-19; Demand Forecasting; Reopening; Health Pandemics; Demand and Consumers; Forecasting and Prediction
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      Balla-Elliott, Dylan, Zoë B. Cullen, Edward L. Glaeser, Michael Luca, and Christopher Stanton. "Business Reopening Decisions and Demand Forecasts During the COVID-19 Pandemic." NBER Working Paper Series, No. 27362, June 2020. (Harvard Business School Working Paper, No. 20-132, June 2020.)
      • 2020
      • Working Paper

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

      By: Laura Alfaro, Anusha Chari, Andrew Greenland and Peter K. Schott
      We show that unexpected changes in the trajectory of COVID-19 infections predict U.S. stock returns, in real time. Parameter estimates indicate that an unanticipated doubling (halving) of projected infections forecasts next-day decreases (increases) in aggregate U.S....  View Details
      Keywords: Covid-19; Stock Returns; Health Pandemics; Stocks; Investment Return; Forecasting and Prediction
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      Alfaro, Laura, Anusha Chari, Andrew Greenland, and Peter K. Schott. "Aggregate and Firm-Level Stock Returns During Pandemics, in Real Time." NBER Working Paper Series, No. 26950, April 2020. (Revised May 2020.)
      • March 2020
      • Supplement

      People Analytics at Teach For America (B)

      By: Jeffrey T. Polzer and Julia Kelley
      This is a supplement to the People Analytics at Teach For America (A) case. In this supplement, situated one year after the A case, Managing Director Michael Metzger must decide how to apply his team's predictive models generated from the previous year’s data.  View Details
      Keywords: Analytics; Human Resource Management; Data; Workforce; Hiring; Talent Management; Forecasting; Predictive Analytics; Organizational Behavior; Recruiting; Data and Data Sets; Forecasting and Prediction; Recruitment; Selection and Staffing; Talent and Talent Management
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      Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (B)." Harvard Business School Supplement 420-086, March 2020.
      • 2020
      • Working Paper

      Market Segmentation Trees

      By: Ali Aouad, Adam Elmachtoub, Kris Ferreira and Ryan McNellis
      As more commerce and media consumption are being conducted online, a wealth of new opportunities are emerging for personalized advertising. We propose a general methodology, Model Trees for Personalization (MTP), for tackling a broad class of personalized...  View Details
      Keywords: Decision Trees; Computational Advertising; Market Segmentation; Online Advertising; Customization and Personalization; Segmentation; Decision Making
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      Aouad, Ali, Adam Elmachtoub, Kris Ferreira, and Ryan McNellis. "Market Segmentation Trees." Working Paper, January 2020.
      • December 2019
      • Case

      Forecasting ClimaCell

      By: Joshua Lev Krieger, Christopher Stanton and James Barnett
      A weather technology startup, ClimaCell considers the R&D trade-offs and financing implications of pursuing a proposed contract with a major automobile maker, rather than continuing its focus on building a scalable, all-purpose weather prediction engine.  View Details
      Keywords: Weather; Forecasting and Prediction; Technological Innovation; Research and Development; Finance; Cost vs Benefits; Decision Making; Strategy
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      Krieger, Joshua Lev, Christopher Stanton, and James Barnett. "Forecasting ClimaCell." Harvard Business School Case 820-044, December 2019.
      • November 2019 (Revised November 2019)
      • Case

      Rechargeable Batteries, 2017: Gigafactory Wars in the Offing?

      By: John R. Wells and Benjamin Weinstock
      In 2017, the global market for rechargeable lithium-ion (Li-ion) batteries was 126 gigawatt-hours (GWh) valued at $37 billion, growing by $10 billion in two years. Once confined largely to consumer electronics and appliances, the rapid increase in demand was spurred by...  View Details
      Keywords: Batteries; Rechargeable Batteries; Lithium-ion; Lithium-ion Batteries; Electric Vehicle; Electric Vehicles; Energy Entrepreneurship; Energy Markets; Energy Storage; Battery; Demand Uncertainty; Demand Forecasting; Supply & Demand; Supply And Demand; Capacity Planning; Tesla; Technological And Scientific Innovation; Technological Change; Technology Change; Technology Commercialization; Policy Change; Subsidies; Power/energy; Power Grid; Energy Policy; Developing Markets; Alevo; Samsung; Lg Chem; Catl; Northvolt; General Motors; Energy; Entrepreneurship; Technological Innovation; Commercialization; Policy; Demand and Consumers; Forecasting and Prediction; Supply and Industry; Emerging Markets; Competitive Strategy; China
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      Wells, John R., and Benjamin Weinstock. "Rechargeable Batteries, 2017: Gigafactory Wars in the Offing?" Harvard Business School Case 720-371, November 2019. (Revised November 2019.)
      • October 2019
      • Case

      GRIT Fitness

      By: Lynda M. Applegate and Olivia Hull
      In December 2018, GRIT Fitness was a growing chain of boutique fitness studios offering a variety of workout classes, including weightlifting, high intensity interval training, and cardio dance. With 400 members and three Dallas studios, CEO Brittani Rettig believed...  View Details
      Keywords: Entrepreneurship; Business Startups; Mission and Purpose; Corporate Strategy; Customer Focus and Relationships; Forecasting and Prediction; Business Plan; Trends; Experience and Expertise; Talent and Talent Management; Training; Health; Selection and Staffing; Leadership Style; Leadership Development; Management Style; Management Teams; Brands and Branding; Organizational Culture; Organizational Structure; Motivation and Incentives; Sports; Competition; Diversification; Expansion; Value Creation; Health Industry; Sports Industry; Texas
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      Applegate, Lynda M., and Olivia Hull. "GRIT Fitness." Harvard Business School Case 820-016, October 2019.
      • August 28, 2019
      • Article

      How to Make Your Sales Forecasts More Accurate

      By: Lou Shipley
      Companies need consistently accurate sales forecasts — but unfortunately they are rare. That’s because many companies fail to align their sales and marketing departments, and that alignment is a prerequisite for forecast accuracy. Companies can achieve better alignment...  View Details
      Keywords: Sales; Forecasting and Prediction; Marketing; Alignment; Technology
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      Shipley, Lou. "How to Make Your Sales Forecasts More Accurate." Harvard Business Review Digital Articles (August 28, 2019).
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      Forecasting & Prediction: Articles, Research, & Case Studies on Forecasting & Prediction– HBS Working Knowledge
      Skip to Main Content Cold Call A podcast featuring faculty discussing cases they've written and the lessons they impart. Subscribe on iTunes 29 Sep...
      The Wisdom of Crowds in Operations: Forecasting Using Prediction Markets
      → Search All HBS Web
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