How Banking Analysts’ Biases Benefit Everyone Except Investors
Wall Street analysts influence markets and companies daily. They release earnings forecasts and investment recommendations moving stock prices and changing investors’ portfolio decisions. These movements in turn generate responses from corporate leaders that make changes in operations, strategies, acquisition, and investment plans. No wonder CEOs and CFOs spend significant amounts of time communicating with the influential analysts covering their firms.
But how unbiased are the earnings forecasts that they release? To answer this question we studied Wall Street analysts that provide earnings forecasts for banks and other types of financial institutions or non-finance companies (‘banking analysts’). We classified all companies that are rated by the banking analysts as likely future employers or not, based on whether they have a sell-side equity department. (Companies with a sell-side equity department hire banking analysts of their own and so are potential future employers.) And we found that banking analysts’ forecasts are in fact biased in favor of potential future employers. Specifically, analysts’ forecasts for these firms are more likely to exhibit “a walk down to beatable earnings.” This is a well-documented pattern where forecasts of annual earnings are optimistic early in the year but become less optimistic later in the year, and then just before the announcement of earnings they are pessimistic. This pattern allows executives to beat their earnings forecasts, which frequently results in large positive changes in the company’s stock price. This pattern is not observed when banking analysts forecast earnings of companies that are not likely to be future employers.
Whether or not they engage in this behavior consciously, analysts do benefit from it — as do bank executives. Analysts issuing more biased forecasts for potential future employers are more likely to face favorable career outcomes and move to a brokerage house of higher status, according to our data. This usually comes with higher compensation and recognition. Moreover, bank executives appear to profit from the analysts’ bias. We find that for banks where analysts are the most biased, executives initiate the largest trades in the bank’s shares following earnings announcements and sell shares following stock price appreciations, pocketing the gains.
So then who loses? Investors, who end up receiving biased expert advice, after paying billions of dollars for these research services, therefore making bad investment decisions. Perhaps this bias in expert advice explains also why an increasing number of investors are conducting their own in-house analysis and rely more on the “wisdom of the crowds” by using signals that are generated by web-based technologies that aggregate individual opinions and measure the sentiment of people towards a company. Moreover, our results raise a number of governance issues. Specifically, board of directors need to carefully evaluate whether stock options and bonuses are awarded for meaningful value creation, not by beating biased expectations.