No, this article isn’t about becoming famous though the internet, the Sisters of the Sororitas, or Famulous Eateries in Bangkok. Rather, I just spent an hour on a Webinar with GMI Ratings on their Forensic Alpha Model (FAM), designed to help investors predict stock returns using forensic-accounting and governance-related measures of issuer risk.
Yes, it was essentially a commercial… but it was very convincing. A few of the facts:
- There is a 14.5% chance that in any given year a company will engage in fraud.
- 42% of boards and senior management are aware of some type of irregular accounting at their firm.
- When made public, corporate fraud costs investors an average 22% of enterprise value.
- Total cost of fraud across all companies is 3% per year, the single largest cost an investor pays.
- The Russell 3000 return 5.67 over the ten year period ending June 30, 2013. Adding back the cost of fraud would have increased that return to 8.67%, an amount that is not trivial.
GMI Ratings doesn’t claim to be able to predict which companies are committing fraud to the extent they can help investors avoid the entire 3%. However, after removing the 25% worst-rated companies from the Russell 3000 (equal weighted) during the period 2002-2012, predicted returns rose from 7.6% to 9.8%, a 2.2% difference and volatility was reduced by 0.8% as well.
How do they do it? Big data analysis, starting with factors such as executive insider’s stock sales divided by total equity compared to peers, CEO + CFO incentive divided by annual compensation compared to industry median, two year volatility relative to peers and 100 metric operations that are statistically correlated with SEC accounting fraud enforcement actions. At least that’s where they start.
Similar findings were presented for Western Europe and Asia Pacific regions. Institutional investors will want to download fact sheets and white papers. Why isn’t removing the riskiest stocks from portfolios a standard part of fulfilling fiduciary duty?