As the election nears, I find myself reading Nate Silver’s FiveThirtyEight blog daily. For those of you unfamiliar with Nate, he is a statistician who tracks the various voter polls. In addition to calculating the consensus of who is favored, he also provides insight about the various polls.
I’m mentioning FiveThirtyEight because in a post yesterday, Nate discussed two statistical concepts that not only apply to presidential elections, but to investing as well. Specifically, he wrote about the difference between bias and accuracy.
Nate posted, “Bias, in a statistical sense, means missing consistently in one direction—for example, overrating the Republican’s performance across a number of different examples, or the Democrat’s. It is to be distinguished from the term accuracy, which refers to how close you come to the outcome in either direction. If our forecasts miss high on Mr. Obama’s vote share by 10 percentage points in Nevada, but miss low on it by 10 percentage points in Iowa, our forecasts won’t have been very accurate, but they also won’t have been biased since the misses were in opposite directions (they’ll just have been bad).”
When it comes to investing, a strong argument could be made for analysts’ recommendations and earnings estimates being far more biased than inaccurate, especially when it comes to short-term forecasts. According to information from Zacks.com, the number of stocks recommended as a “buy” or better outnumber those recommended as a “sell” or worse by a margin of nearly 30-to-1. Thomson Reuters says 63% of companies have topped third-quarter earnings expectations. (The number is based on the 272 S&P 500 companies that have reported through last Friday; a more current number has not been released yet.) This earnings “beat rate” is higher than the long-term average of 62%, but lower than the average over the past four quarters of 67%.