The New York Times has an article today about how the CEO at Freddie Mac ignored the warnings signs of potential problems, in particular its financing of questionable loans that threatened its financial health. Not necessarily news, and you can decide who you want to believe, but it once again stresses the need for not only implementing a risk management system within companies, but actually listening to the recommendations offered by the chief risk officer. Insiders at Freddie Mac say that the CEO of Freddie Mac, Richard Syron, made things worse by repeatedly ignoring recommendations from the chief risk officer at Freddie, David Andrukonis, regarding poor underwriting standards that were becoming too weak and too risky.

Andrukonis is quoted as saying:

“The thinking was that if something really bad happened to the housing market, then the government would need Freddie and Fannie more than ever, and would have to rescue them. Everybody understood that at some level the company was putting taxpayers at risk.”

Moral hazard at is best, or ugliest. Of course, this comment is not quite as telling as the one made by CEO Syron, who contends:

“If I had better foresight, maybe I could have improved things a little bit. But frankly, if I had perfect foresight, I would never have taken this job in the first place.”

While none of us has 20-20 business vision, the need for better insight is exactly why companies need to utilize some type of risk management. Although not a perfect science (far from it), risk management can at least provide managers some of that needed foresight. While the future cannot be forecast at a level that makes it easier to sleep at night, risk management can at least provide scenario analysis supported with statistics and various risk measures, among other techniques, that will give managers some idea of where potential problems lie so that safeguards can be taken (such as increasing capital or laying off risk) and corrective action can be planned and anticipated.

It appears that Wall Street and Corporate America are getting the message as companies struggle to educate themselves on enterprise risk management, implement risk management systems, and hire employees with the proper risk management skills. Understanding credit risk, market risk, operational risk, Value-at-Risk, Basel II, RAROC, and GARCH volatility modeling are causing businesses to seek out universities and consultants as they rush to receive the needed education and training. Of course, like TQM in the 1980s and 1990s, it is up to businesses to actually practice what they preach, or at least practice what they put in place. Fortunately, for those interested in risk management, challenges and job security will be available as innovation and capital growth offer new problems for businesses. Hopefully, it will not take another Bear Stearns, Freddie, or Fannie in a few years to once again drive the point home.

As I was browsing various blog sites I came across an article entitled "What is High Implied Volatility?" at the VIX And More blog. The article is worth a read, and is linked above, but I wanted to mention and elaborate on a simple concept from the article that often gets overlooked. As traders and professors we often instruct students and others about how we can compare implied volatility to historical volatility to see whether an option is over-price or under-priced, assuming that the historical volatility is constant, and that it will stay that way into the future. Of course, comparing the two in real-life without such assumptions can be a little more complex.

As described at VIX and More, we need to compare the current implied volatility with a defined range of either historical volatility or implied volatility. Of importance are the time frames used, the type of past volatility (historical or implied), and the comparison universe (the same stock and/or similar stocks). Furthermore - and this is the key - we must not forget that historical volatility is by definition, and calculation, backward looking. On the other hand, implied volatility is forward looking and considers the market's expectation and potential reaction to news and events, such as earnings, dividends, FDA phase testing results, Federal Reserve actions, etc.

To make life easier, sometimes a relative measure, even one that considers a range or moving average, is useful. For those with a little more background and interests in mathematics and modeling, one of the many variations of the Generalized Autoregressive Conditionally Heteroskedastic (GARCH) models, or stochastic models of implied volatility surfaces, can be used. Other models also exist. I have used GARCH and find it to be useful when constructing option spreads, although parameter selection is necessary. With the right software, even a pre-programed Excel spreadsheet, the analysis can be implemented with less pain than expected, and sometimes incorporated into defined trading rules for those platforms that allow such integration.