By Jay Akasie
| (Illustration by Shout) |
Damian Handzy received an e-mail from the headmaster of his son’s school that detailed the events surrounding a recent fire there. After a plume of smoke set off the alarms, the students and teachers safely evacuated the building, based on a drill they’d been practicing regularly, while the fire department arrived and extinguished the smoldering remains. The incident got Handzy, the CEO of Berkeley Heights, New Jersey–based Investor Analytics, thinking about his son’s school having a better sense of risk mitigation than many of the leading participants in the capital markets.
“The administrators figured out what could go wrong during the course of a school day and how they would respond to events like a fire,” he explains. “Yet there are no across-the-board best practices in the financial world set up to respond to things like stock market crashes or credit crunches.”
That’s not to say hedge fund investors aren’t setting up their own versions of a financial fire drill. Once the exclusive realm of the largest and most sophisticated fund-of-funds managers like Blackstone Alternative Asset Management and UBS, the technology driving risk analytics has become commoditized, with off-the-shelf software packages widely available to investors of all sizes. Outfits such as HedgeMark Risk Analytics, Imagine Software, Inalytics, Investor Analytics and PerTrac sell versions of risk mitigation software that give any investor the chance to assess exactly how its hedge funds would react to extraordinary events.
The shift in risk management marks a move away from statistical analysis in favor of stress testing, according to Lance Smith, CEO of Imagine Software. A Monte Carlo simulation endures as one of the most popular stress tests because it allows an investor to test multiple scenarios with a host of random variables, not unlike those in the casinos in the glitzy Mediterranean port for which it’s named.
Stress testing lets investors gauge the resilience of even the most unexpected set of risks in a portfolio. These days it’s not uncommon for the technology of risk analytics to test scenarios that have a standard deviation of as much as eight or nine. (Anyone who’s ever suffered through a statistics class knows that standard deviation is a measure of the distance from the statistical mean.) An event with a standard deviation of eight or nine falls near the very tip of the long tail.
One of the long-used products of the statistical approach — Value at Risk, or VaR — relies on historical price data to construct a distribution of probable outcomes for a portfolio. But an inherent problem with VaR is how to estimate correlations between the historical prices of stocks and volatility in the market.
“You’re using historical data to estimate what correlations will be between prices and volatility,” says Smith, whose company is headquartered in New York and has offices in Hong Kong, London and Sydney. “That results in a probable distribution of probable outcomes.”
In the months leading up to the collapse of Lehman Brothers Holdings, the Wall Street firm was reporting VaR analyses every quarter that yielded sums in the hundreds of millions of dollars. “Yet Lehman lost $40 billion in September of 2008,” says Rick DiMascio, the CEO and founder of London-based Inalytics. “How can that have been the case? And why do some firms just continue carrying on using VaR and believing it?”
Finding the right tool to test for risk is not lost on Kenneth Phillips. In the midtown Manhattan headquarters of HedgeMark, the risk analytics firm he founded, he displays his collection of antique mathematical instruments, including a giant slide rule and protractor that were once used to teach children.
Phillips was managing a handful of funds of funds a decade ago when he began hearing the same thing every time he interviewed fund managers and attended industry conferences: The hedge fund industry had grown so popular that investors were finding it more challenging to find funds that could best buoy their portfolios from a wide range of risks. “Understanding the hedge fund industry takes on a new meaning when you run a fund of funds yourself,” he says.
Phillips says he began sensing that the industry was growing to a point where a broader base of investors — pension funds and other institutions — with a wide exposure to diversified portfolios were desperately trying to find new ways to monitor fund managers. Part of the initial appeal of investing in a hedge fund, of course, was the sort of high and noncorrelated returns that the largely unregulated funds could generate.
With those benefits, however, came managers who had inordinate amounts of discretionary power over how a fund is managed, redemptions are processed and fees are calculated.
The industry’s transformation during the past decade led Phillips to reassess just what risk meant to investors. For him, the traditional returns-based methods of analyzing risk weren’t sufficient. So he began to devise a position-based risk system that would allow an investor to calculate VaR on a daily level but also to run scenario modeling and stress testing. “If you run a Monte Carlo simulation to test returns, you’re going to find out that you face a 70 percent chance of loss,” says Phillips. “But you won’t have any idea of the circumstances that lead to that loss.”
In 2009, Phillips launched HedgeMark, the result of more than three years of research and development by a team of 30 analysts and computer engineers. The idea was to take risk analytics to the next level by providing granular data about markets, industries, sectors and geopolitics to the investor at both an aggregate and an individual level. “Transparency can be a very powerful tool in the hands of a knowledgeable, talented person,” he says.
After looking carefully at existing risk analytics platforms and how they were developed, Phillips says he came to the conclusion that there was plenty of room in the industry for a fiduciary platform rather than a structured-product platform; he hooked up with Bank of New York Mellon to offer fund analytics and management rather than simply sell firms software packages. With comprehensive risk analytics as its foundation, HedgeMark could address problems that Phillips wanted addressed for himself.
For instance, he designed HedgeMark’s compliance and surveillance modules so that users have the flexibility to define their own risk exposures and concentration limits. More important, he designed the software to analyze what circumstances would lead to a loss.
“If you have software that tells you there’s a 10 percent chance that you’ll lose 50 percent of your portfolio’s value, you need to know what types of external events could lead to that 50 percent drop,” Phillips explains. “Otherwise you don’t know how to mitigate the threat and hedge it out properly.”
Risk analytics are popular with pension funds, endowments and other institutional investors, says Lisa Corvese, the head of global business strategy at PerTrac, one of the industry’s oldest hedge fund analytics firms. “Let’s face it: Alternative investments aren’t so alternative anymore,” says Corvese, whose firm’s software is used by both hedge fund investors and managers. “Hedge funds are more important than ever to the overall alpha of a portfolio.”
Corvese says that PerTrac’s performance measurements have always been designed with the institutional investor in mind. But in the post–Bernard Madoff era, there is more of an onus on hedge fund administrators to report to investors. Valuation and pricing have become of paramount importance to clients.
The ability to fine-tune a fund of funds is no less important. Because each institution has its own investment profile that it’s trying to achieve, risk analytics software helps a manager narrow lists of funds to a final few that use the right strategy. The latest tools also help investors try to determine when to get in and out, allowing clients, for instance, to scrutinize a fund’s cash on hand.
PerTrac offers clients more than 900 performance-based statistics, from simple monthly return streams to templates that chart compound rates of return, standard deviation and Sharpe ratios. The New York–headquartered firm has been around since 1996, but it still offers a vast array of analytics tools for the desktop computer. When databases need updating, PerTrac utilizes cloud-based systems to do so.
“We’re all about helping the investor understand what his portfolio would look like in a fat-tail world,” says Corvese.
