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Financial markets benefit from in-depth analysis of firms’ earnings

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News articles that analyze firms’ earnings calls have a greater impact on financial markets than articles that simply disseminate information contained in firms’ press releases. This suggests that investors benefit from more in-depth analysis of quarterly earnings announcements, MIT Sloan PhD student Nicholas Guest shows in new research.

Guest won the 2018 MIT Sloan thesis prize April 4 for his paper, “Do Journalists Help Investors Analyze Firms’ Earnings News?” Guest compared articles about earnings announcements for select S&P 500 firms in The Wall Street Journal to company press releases about the announcements.

The fewer similarities between the article and the press release, the more analysis the article provided, Guest said. This could include macroeconomic context, background information about the company, or news about layoffs or executive changes, he says.

When these in-depth articles appeared in The Journal, trading volume increased for the companies covered, as investors were better able to gauge a firm’s prospects, Guest said. In the summer of 2017, for example, Under Armour’s earnings announcement noted that the firm beat Wall Street expectations — but an in-depth article noted the company’s plans to lay off nearly 300 employees. Under Armour stock lost 8 percent of its value on the news.

How to model product demand

Firms often struggle to set the optimal price and determine the ideal production volume for a new product due to a lack of historical data. Offering hypothetical choices through an informal poll leads to inaccuracy, while selling actual products at non-optimal prices can be costly.

New research from PhD student Xinyu Cao shows the benefit of performing an incentive-aligned experiment, which offers prospects who are willing to buy a new product for a particular price an opportunity to buy at that price through a lottery.

Cao earned the second place thesis prize for her working paper, “Prelaunch Demand Estimation [PDF],” which details an experiment conducted on a popular smartphone soccer game in China. 

Users were offered the option to buy a package of six high-quality players at a range of costs between $16 and $32, with a range of odds that they would win the lottery for the chance to buy the package. In the model developed using data collected in the experiment, the extrapolated likelihood that a user would purchase the package compared to the benchmark with only a very small margin of error, Cao said.

Guest received $3,000 for first place. Cao receive $2,000 for second place. The pair presented their work April 3 on campus to a panel of three judges: Nitin Joglekar, PhD ’97, Winston Dou, PhD ’17, and Joshua Krieger, PhD ’17, who won last year’s prize for research on how companies can learn from their competitors’ research and development failures.

Four other PhD candidates and one gradaute presented research at the event:

  • Yixin Chen, “Individual Stock-piling Skills in Active Mutual Funds.”
  • Jorge Guzman, PhD ’17 “Go West Young Firm: The Value of Entrepreneurial Migration for Startups and Their Founders.”
  • Arvind Karunakaran, “Front-line Professionals in the Wake of Increased Digital Scrutiny: Examining the Paradox of Public Accountability.”
  • Minjae Kim, “A Man Is Known by His Cup: Signaling Commitment via Insecure Conformity.”
  • Heidi Packard, “Are Long-Term Earnings Target Forecasts?”

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