Risk Calculators: Finance Geeks Use Open API to Crunch Market Numbers

Alpha geeks Jesper Andersen (left) and Toby Segaran Photo: Joe Pugliese When AAA-rated companies began crumbling like sand castles in an earthquake last year, Jesper Andersen and Toby Segaran had the same thought: There has to be a better way of measuring corporate credit risk. Bond rating is plagued by insularity, they argue. Agencies like Moody's […]

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Alpha geeks Jesper Andersen (left) and Toby Segaran *
Photo: Joe Pugliese * When AAA-rated companies began crumbling like sand castles in an earthquake last year, Jesper Andersen and Toby Segaran had the same thought: There has to be a better way of measuring corporate credit risk.

Bond rating is plagued by insularity, they argue. Agencies like Moody's and Standard & Poor's lack transparency, use narrow data sets, and rely on too few models (one of which was the notorious Gaussian copula formula featured on Wired's March cover). Worst of all, they're paid by the firms they evaluate—an obvious incentive for grade inflation. "No one can pay for this and keep it fair," Segaran says.

The partners' solution: a volunteer army of finance geeks. Their project, Freerisk.org, provides a platform for investors, academics, and armchair analysts to rate companies by crowdsourcing. The site amasses data from SEC filings (in XBRL format) to which anyone may add unstructured info (like footnotes) often buried in financial documents. Users can then run those numbers through standard algorithms, such as the Altman Z-Score analysis and the Piotroski method, and publish the results on the site. But here's the really geeky part: The project's open API lets users design their own risk-crunching models. The founders hope that these new tools will not only assess the health of a company but also identify the market conditions that could mean trouble for it (like the housing crisis that doomed AIG).

"This problem is too big to leave to private profit centers," Andersen says. With its network of number nerds, Freerisk may just create the metrics we've been missing.

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