Predicting Bankruptcy
Tuesday, April 3, 2012
By MATT ELLIOTT
Markets don’t lie. Probably.
That’s part of the Efficient-Market Hypothesis.
No matter what manner of shenanigans, skullduggery or tomfoolery corporations engage in, the market knows and sees all. Prices reflect that knowledge. Stock prices. Option prices. Et cetera. Theoretically.
Realizing that, two OSU finance professors, Betty Simkins and Antonio Camara, have taken a popular way to price options – the positions people take when they buy stocks – and tweaked it to measure bankruptcy risk.
They compared their results against cases of big bankruptcies during 2007 and 2008 financial crises and found their system was as accurate as Moody’s KMV, the biggest Wall Street credit rating system, and sometimes beat the popular rating method, Simkins says.
Also, in every case it was more accurate than methods used by credit rating agencies. They published their results in a 2011 issue of the Journal of Banking and Finance.
“Ours certainly won’t replace the others, but it will be useful if anyone wants another measure — a forward-looking measure of bankruptcy risk,” Simkins says.
Developing the Model
Camara and Simkins began working together on the model after he was hired at OSU in 2006. Their initial focus was on historic bankruptcies.
“We were curious if we might be able to find early evidence with Enron or other companies,” Simkins says.
They started with the Black-Scholes model used to set option prices, the value of stock bought and sold on the market.
Option prices rise and fall according to how the market views companies’ viability. If certain kinds of options go up, that indicates the market expects companies to do well.
Simkins and Camara figured those prices would detect things credit rating systems wouldn’t. That’s because most rating systems test companies using historical information such as accounting data that looks only at what happened previously.
However, a key drawback to the Black-Scholes model is it makes a few unrealistic assumptions. Chief among those is it assumes there’s no bankruptcy risk with the company behind the option in question.
Simkins and Camara found a way to make the equation account for that. Enron was one of their big tests.
Test Cases
Before WorldCom went under in 2002, no bankruptcy was bigger than Enron when it collapsed in 2001. It vaporized employee 401ks and shook the economy to its core roots while raising questions about deregulation.
The OSU model found Enron’s bankruptcy likelihood shot up in February and March 2000. Funny thing is Enron’s credit rating was still “investment grade” just a year before its collapse.
“Were the option prices picking it up earlier than other measures? There is some evidence of that,” Simkins says.
In other cases, the group looked at companies that were simply sick and not committing fraud, such as Dana Corp. More than six months before Dana Corp. failed in 2006, the OSU model found the company’s bankruptcy chances had skyrocketed to around 30 percent.
But just because the risk shot up, their model didn’t always predict bankruptcy. That’s because option prices can reflect a market’s volatility, or a sudden bout of skittishness toward risk, as it reacts to breaking news.
As scandals and the like become old news, the market moves its prices toward their true levels.
A key example of that was Tyco International, the alarm and fire protection company. CEO Dennis Kozlowski and CFO Mark Swartz were convicted in 2005 of grand larceny and securities fraud. The company didn’t go bankrupt, but the OSU group’s model showed increased chances of bankruptcy – the market’s immediate, gut-level reaction to developing news of the scandal. Years after the scandal, Tyco remains a viable company.
Subprime Crisis
The paper was headed to print in 2008. It won the best paper award from the Financial Management Association. However, a reviewer with the Journal of Banking and Finance asked Simkins and Camara to instead look at the subprime mortgage crisis that began in 2007.
Low interest rates, rare regulation, toxic mortgages, easy credit and a financial industry saddled with $36 trillion in debt conspired with excessive borrowing, risky investments, lack of derivatives transparency, failed corporate governance and falling lending standards to cause the biggest recession in more than 80 years. American households would lose at least $11 trillion in wealth. The recession it triggered continues to harass economies all over the world.
That’s according to the federal government’s Financial Crisis Inquiry Report released in January.
“It’s kind of sad,” Simkins says, “but our timing was perfect.”
Simkins’ group, joined in 2008 by Texas State’s Ivilina Popova, studied the crisis for another two years. Their results were the same. They found a much higher bankruptcy risk of companies studied.
Also, just as in the earlier bankruptcy study, Simkins, Camara and Popova predicted bankruptcies with greater accuracy than credit rating agencies such as Standard & Poor’s. They also replicated Moody’s system (as much as they could since part of the method is kept secret), calibrated it to account for derivatives and improved its accuracy.
So-called “over-the-counter derivatives” were part of a “shadow banking system” full of short-term debt that was nearly as large as the traditional banking system, the government reported. Regulations built to prevent panics that caused banking mayhem since the 19th century couldn’t regulate derivatives, a multitrillion-dollar repo lending market and other things not shown on companies’ balance sheets.
The government in part blamed the derivatives market for the crisis, as well as actions of huge financial institutions such as failed investment banks Lehman Bros. and Bear Stearns. Simkins, Camara and Popova compiled companies’ derivatives exposure by combing footnotes to annual reports, Securities and Exchange Commission’s 10-K reports and other areas.
Simkins and the others had to piece together companies’ derivatives exposure to get a more-or-less complete view of their bankruptcy risk. Tragically, Camara died from lung cancer before the article was published, leaving behind a wife and two children.
Simkins, lamenting her friend and colleague didn’t live to see the work finished, says it’s possible their model could help rating agencies better predict bankruptcies. It works with all kinds of companies, including financial firms not rated by systems such as the Altman Z-score.
Simkins knows other folks in academia are using it in research. She’s not so sure about industry because the work was published in detail. Any reader could replicate the approach and use it.
“That’s the purpose of academic research. We tell them how to do it all because we’re not trying to sell it or do anything other than communicate there’s another measure of credit risk. I definitely think it makes an important contribution.”
Finance professor Betty Simkins holds the Williams Companies Professorship of Business and has been at OSU since 1997. She is co-editor of the Journal of Applied Finance and editor of FMA Online, the online journal for the Financial Management Association. Before she obtained her doctoral degree from Case Western Reserve University, Simkins worked for Williams and ConocoPhillips in corporate financial planning, research and development, and process engineering. She is co-editor of a popular textbook published in 2010 called Enterprise Risk Management: Today’s Leading Research and Best Practices for Tomorrow’s Executives.
Antonio Camara was a former business reporter in Portugal before beginning his academic career in Lisbon at Universidade Tecnica de Lisboa. His research has appeared in The Journal of Finance and The Journal of Banking and Finance. He also received the Richard W. Poole Research Excellence Award, which honors faculty members published in leading research journals, and the Best Paper in Risk Management Award from the Financial Management Association, the award he shared with Simkins for their bankruptcy study. He died in 2011.