I came across this interesting line in a “CNN report”:http://money.cnn.com/2009/07/31/markets/sunday_weekahead/index.htm yesterday discussing explanations for the July bull market. Here was the basic argument:
bq. With over two-thirds of the S&P 500 having already reported results, profits are currently on track to have fallen 29% versus a year ago, according to earnings tracker Thomson Reuters. Clearly, profits are still suffering amid the recession, but the results were expected to be worse. As of July 1, analysts were expecting year-over-year results to fall more than 35%. Although led by financials, results have been beating expectations pretty much across the board, said John Butters, senior research analyst at Thomson Reuters. . . . “The theme is still that we are seeing an unusually high number of companies beat expectations,” said Butters.
Fair enough. But it was the next line that caught my attention:
bq. Around 74% of companies have beat forecasts, versus the _long-term average of 61%_ (empahsis added) and the all-time record of 73%, reached in the first quarter of 2004.
Now I might be missing something here, but if the forecasters were good at their jobs, shouldn’t the long term average of companies beating forecasts be the same as the long term average of companies doing worse than the forecasts? If we assume that it is impossible to actually get the forecast correct on the nose (e.g., all profits either beat or fall short of the forecasts), then that means 61% of the time companies exceed forecasts and 39% of the time they undershoot them, which is better than a 3:2 ratio. And that’s the most conservative estimate. If companies actually hit the estimates exactly some of the time and beat them 61% of the time, then the ratio could be even higher.
What could account for this systematic bias? Incompetence seems the most benign explanation. What is potentially a little more troubling is if the “industry” knows that what when companies overshoot profit estimates stocks go up and the “industry” benefits, and thus there is some for of systematic pressure on analysts to consistently bias profit estimates downwards to create this effect. I’m sure there is plenty of research out there on this in the financial markets literature, so I’d be interested to hear from someone who knows more about this than I do. But as someone who is used to looking at statistics, this one really jumped out at me.