How We Calculate Earnings Distortion Scores

As a short-term predictor of the likelihood of a company to miss expectations in the next quarter, our Earnings Distortion Score compliments, but does not override, our longer-term Risk/Reward ratings.

We measure Earnings Distortion (as featured on CNBC Squawk Box) based on our proprietary and superior fundamental data. Core Earnings: New Data & Evidence, forthcoming in The Journal of Financial Economics, proves the superiority of our data and models.

We leverage our superior dataset of unusual gains/losses to derive Earnings Distortion Scores for ~3,000 stocks. These scores indicate how likely companies are to beat or miss estimates based on how much unusual gains/losses cause unadjusted earnings measures to be over/understated.

The Earnings Distortion Score formula is: Core Earnings Distortion divided by Total Assets.

We decile these values and, then, categorize into a 5-tier scoring system:

1. Strong Beat – Top decile (Least earnings distortion)
2. Beat – Second and third Decile
3. In line – Fourth, fifth, sixth and seventh decile
4. Miss – Eighth and ninth decile
5. Strong Miss – Bottom decile (Most earnings distortion)

We scale core earnings distortion by total assets so large companies don’t dominate the rankings, as they are likely to have more earnings distortion simply due to their size. Further, this approach mirrors the strategy in “Core Earnings: New Data and Evidence”, which presents a long/short strategy that delivers abnormal returns of 7-10% annually based on our proprietary Earnings Distortion data.

Our Earnings Distortion Scores empower investors to combat management manipulation of earnings. For more on how to use our Earnings Distortion Scores, click here.

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