CEO language misleads analysts’ ratings, study confirms

charismaBusiness analysts, who are paid to dryly evaluate and forecast the financial performance of the companies they cover, turn out to be vulnerable to what one research group has dubbed “charismatic” language in the CEOs’ vision statements.

Certain words and imagery seems to push analysts’ emotional buttons. These analysts then skew their forecasts, misleading investors to believe a company’s earnings potential will be higher than it actually is.

The end result: Carefully wording a CEO’s communications a certain way can boost the stock price of a company. This eventually causes investors to lose money, when quarterly results don’t match the chief executive’s abstract vision or the analysts’ numeric ratings.

The study was carried out by INFORMS, the Institute for Operations Research and the Management Sciences in Hannover, Maryland.

When the study talks about  charsimatic language, it doesn’t mean personal charm. It means using specific patterns and keywords when talking about the company’s past, present and future.

The researchers analyzed the initial letters to analysts sent by new CEOs at 367 companies. They dubbed as charismatic any language in those letters that followed these three patterns:

  • Criticism of the status quo. “Awful … terrible … disappointing.”
  • Ideological terms when speaking of goals. “Believe … commitment … change … right … necessary.”
  • Empowerment of the stakeholders. “We … us … team.”

The study validated two of the researchers’ three scientific hypotheses:

  • Charismatic initial communications from new CEOs to analysts leads to more positive ratings from the analysts.
  • A herd effect causes other analysts to follow along and also issue more favorable forecasts.
  • This theory was only partially validated: Within one year following a high frequency of charismatic communications from a CEO, analysts made larger errors — both overrating and underrating —  in their forecasts of the company. A charismatic CEO can cause investors to lose money by falsely boosting the numeric expectations of the analysts whom stock traders trust.

Vilmos Misangyi of Pennsylvania State University, one of the three researchers, explains the concept in this video clip: