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Mass in motion

Risk management's popularity may make it less useful. Observing a phenomenon can change it.

Risk management's popularity may make it less useful. Observing a phenomenon can change it.

By Andrew Capon
January 2001
Institutional Investor Magazine

Risk management's popularity may make it less useful. Observing a phenomenon can change it. That's a gross simplification of Nobel Prize-winning physicist Werner Heisenberg's uncertainty principle, but it does capture a key concern about the growing use of risk management techniques in the financial markets. Although Heisenberg was addressing an obscure problem in subatomic physics in 1927, financial risk managers today are reaching a similar conclusion: Measuring the risk inherent in a transaction may end up distorting the risk.

The worry, say numerous academics and portfolio managers, is that as risk management tools are deployed by more and more investors - including a wide range of financial institutions - they may become less effective. That's because investors tend to move en masse, and this herding effect seems, in the short term at least, to increase both volatility and correlation, the extent to which asset classes move together. These are two problems that risk management is supposed to solve.

This news isn't all bad for investors, though. After all, contrarians can find opportunities in these distortions. As Lee Thomas, senior international portfolio manager at California-based Pacific Investment Management Co., puts it, "What we should be doing is buying when markets become outrageously depressed, because everyone is trying to exit at the same time and selling back to the market when confidence returns."

In a recent paper, which won the prestigious Jacques de Larosire award from London's Institute of International Finance in October, Avinash Persaud, head of global trading and research at State Street Bank, explores the effects of lockstep investor moves. "In a world of herding," he writes, "tighter market-sensitive risk management regulations and improved transparency can turn events from bad to worse, creating volatility, reducing diversification and triggering contagion."

Since many banks, which were among the first practitioners of risk management, follow the same risk guidelines, they tend to react in a pack. A small rise in the volatility of a certain asset, for instance, might cause a handful of institutions with large exposures to begin selling as their internal risk alarms go off. That, in turn, could send the value of these assets still lower, tripping risk alarms at still more financial institutions, which then sell. All of a sudden a stampede is under way.

"The predominance of herding behavior and its lethal combination with the practice of [risk] limits explain why the 1990s have been such a decade of financial dislocation: the financial system has been in crisis for 40 out of the 120 months, or 33 percent of the time," Persaud writes.

Though crude forms of risk management have been around for decades, the science came into its own in the early 1990s, when regulators, notably E. Gerald Corrigan, then president of the New York Federal Reserve Bank, grew increasingly chary of the large off-balance-sheet risks banks were running in their swaps and derivatives books. "How much can you lose in a day?" became the regulators' critical question to the banks.

In response, banks came up with the notion of value at risk, which measures potential loss exposure at a specified level of confidence. So, for example, a one-day VAR of $1 million with a 95 percent confidence level means that on five trading days out of 100, the bank would expect to lose $1 million. Banks also commonly use a variation on VAR: daily earnings at risk.

By the mid-'90s, as financial risks grew larger and more complex, the risk management movement spread from banks to other financial services companies. The discipline not only became more pervasive, it also grew more sophisticated. A whole new industry of software providers offering better measurement tools was born.

As the software proliferated, so has the evidence of periodic bouts of investor hysteria. Persaud's paper draws upon examples from the currency markets. If a crash is defined as a 10 percent fall in the real exchange rate over three months, Persaud estimates that these markets have experienced 78 crashes in 72 countries since the European Monetary System crisis began in September 1992. Not surprisingly, some 70 percent of the crashes occurred between 1995 and 1998 (Asia, Brazil, Russia), with the contagion spreading based on investor, rather than trade, flows.

The distribution of daily market returns is also telling. A risk manager looking at the daily returns of a portfolio of OECD currencies versus the dollar over the previous five years in January 1997 would expect to see a 1 percent-plus daily decline in the value of his portfolio about 5 percent of the time. Three years later the same portfolio would have daily declines of that size more than 10 percent of the time.

Bluford Putnam, formerly CIO at CDC Investment Management Corp. and Bankers Trust Corp., who now runs Bayesian Edge Technology and Solutions, a risk management software and consulting firm in New York, suggests that the U.S. high-yield market may be a current victim.

"Wider spreads have triggered losses in many [collateralized debt obligations], which have resulted in risk measurement violations in the covenants of the CDO, causing simultaneous forced sales, further pushing spreads wider, forcing more sales," says Putnam. CDOs, a by-product of securitization, are funds sold to institutional investors that invest in a variety of lower-rated corporate paper and loans. They are generally leveraged.

How might a contrarian investor best exploit the effects of herding?

Because they are unregulated, hedge funds might be best positioned to profit from mass investor shifts. But even they are indirectly subject to the new rules of risk management. Hedge funds usually receive their leverage from firms like investment banks that use risk measurement systems. If the investment bank's risk managers are telling its own traders to cut positions in a volatile market, it's unlikely another branch of the firm will provide leverage to a hedge fund operating in these same markets.

Institutional fund managers have taken note of the trend and are trying to figure out ways to exploit it. Says Pimco's Thomas, "Large funds such as ours are actually well suited to make money from herding because we have longer time horizons."

But Thomas and other managers also say it's equally important to understand what's causing a major alteration of investment flows. "You don't want to be caught in a paradigm shift," says Thomas, that means fundamental, long-term valuations have changed. If there are signs of distressed selling, and market feedback indicates bank traders are cutting positions, "you may see unusual value," he says. "The key is knowing when there is a paradigm shift and when it is simply a periodic market panic."

Some managers are experimenting with ways to account for the impact of herding - while still living within the bounds of their own risk management systems. Ram Willner, director of quantitative research and international fixed income at Bank of America Capital Management in Los Angeles, for instance, uses the J.P. Morgan emerging-markets bond index as an early warning signal of future volatility in developed government bond markets, where he manages money. As volatility in the EMBI ticks up, Willner anticipates changes in his own portfolio. Correlation and volatility tend to rise together, so the ability to diversify will diminish as many markets become turbulent.

At this point, the instinct of the average trader would be to flee. "But I don't do that," Willner says. "As others are cutting back, I see my buying opportunity."

Even so, he applies his own risk standards in these situations. He sets a threshold for the increase in volatility and correlation that he can endure. If the risk signals stay below the threshold, he keeps buying. Above the threshold, Willner says, and "I start to think about selling risk positions and buying safe haven assets."

As they seek opportunities in volatile markets, both Thomas and Kenneth Yip, head of research at Deutsche Asset Management, have been following advances in "extreme value theory." Developed over the past decade in the insurance industry, extreme value theory tries to provide the most accurate kind of worst-case scenario. A volcano can wipe out an insurer's profits for the year, but sovereign default can hit a fund manager with equal force.

Thomas's own research suggests that risk management would be more effective if it recognized that markets have "two states." This theory suggests that markets move very little most of the time but quite a lot for very short periods. "Over a long period of time, all the returns come from 5 percent of the time periods. For 95 percent of the time, nothing happens to your total return," he says.

That doesn't mean portfolio managers can spend 95 percent of their time working on their tans. Preparing for the next 100-year storm requires constant monitoring. As Heisenberg noted nearly three quarters of a century ago, uncertainty reigns.