Seven Questions for Damian Handzy, CEO of Investor Analytics

March 30th, 2010
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Contributed by: Andrew Saunders, EFX Prime Services
In the words of a friend of mine, the business of risk “is brisk.” One of the reminders of 2008 was that in times of stress, correlations do indeed go to one, and many of the tools available fail miserably. Here to offer his insights into the evolving nature of risk management tools is Damian Handzy, Chairman and CEO of Investor Analytics. In January, Investor Analytics was awarded Risk Magazine’s 2010 Software Product of the Year. Damian has set himself apart in the industry by incorporating advancements from related disciplines to improve risk management – especially lessons from Natural Selection / Evolution, Cognitive Science, and Behavioral Economics. His academic background and preparation for IA includes undergraduate work at the University of Pennsylvania and he received a PHD in nuclear physics while working on correlation functions at the National Superconducting Cyclotron Laboratory in Michigan. He considers himself a “fully recovered physicist.”

Q1: What’s driving business for IA? Investors seeking tools or managers seeking additional risk transparency to show investors?

Ultimately, the demand comes from investors’ need for better risk management – they want their managers to perform better risk management, which translates in large part to more transparency, and they want to have access themselves to some of the tools/analyses.

Investors no longer accept the “trust me” argument, and they are no longer under the impression that all managers have proper and comprehensive risk management capabilities. So, they are demanding that managers improve the quality of the risk management they perform and they are simultaneously demanding for direct access to some of the risk management output.

Pre-2008, there were many firms that only paid lip service to risk management. These firms may have had risk systems, but they were mainly used by the marketing departments. For those firms who actually did perform risk management, many did not give enough authority to the person responsible for controlling the risk. All this has changed now, as risk is a topic that crosses the CEO’s desk.

Most importantly, many people are recognizing that risk management is not “simple” and that trying to neatly stuff it into one number (like VaR) or trying to do it quarterly is just not going to work. Part of this is the recognition that models cannot capture every possibility and that just because a model produces an output, it doesn’t mean that the output is accurate or appropriate. Human judgment is a very important part of the risk management process.

Q2: What is your perspective on the future prospects of financial engineers? Did the quants get it all wrong?

Blaming the quants / financial engineers is too easy. Suggesting that financial engineering is “going away” is like suggesting that medical doctors have no future after a pandemic, like the 1918 Influenza disaster. The truth is that many firms managed to navigate the financial crisis rather well – in part because their financial engineers knew what they were doing. Unfortunately, many firms did not make it through so easily, and these grab the headlines.

Financial engineers/quants can be divided into two camps: those that devise new securities to trade and those that devise new methods to value securities and analyze their risk. The first group is possibly better described as “quant traders” and the second group as “risk managers.”

Quant traders will continue to innovate new ways to invest – inventing both new strategies and new securities. Traders are in the business of coming up with new sources of alpha, and that will not stop. So by definition, the quants who design risk measurement techniques are always one step behind the traders who design new securities. How far behind depends on how complex the securities are. Worst case example: pooled and collateralized asset back securities with several hundred tranches. Some of these literally take a team of experts up to a year just to come up with an estimated value to an acceptable accuracy. It is physically impossible to do this much faster. Best case scenario: The security is “close enough” to an existing scenario that you don’t lose much in using the alternative model – but this decision is a slipper slope and can lead to oversimplified assumptions overlooking important risks.

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