Hedge Fund Risks: Measurement vs. Management

Author: Seeking Alpha.com
The other day I was telling a colleague that my lawn has become brown. His response was that the color of my grass did not matter as long as the neighbors 'grass on either side of me was uglier.
While this model may work for lawn supremacy, it does not hold in the hedge fund world. You can’t claim your risk measures work because your neighbor’s risk management is worse. Frankly, when it comes to risk it is better to follow Warren Buffett’s advice, “It takes 20 years to build a reputation and five minutes to ruin it." If you think about that, you'll do things differently.

Risk in the hedge fund world comes from two primary sources – market risk (which is a function of portfolio, liquidity, leverage, and counterparty risk) and operational risk (or the interaction of people, process, system, and data). I also refer to operational risk as manager risk. From a market risk perspective, funds use a variety of risk measures. The most frequently used is Value At Risk or VAR. VAR emerged as a flagship technique because it provides a single number (based on a confidence level) that represents a potential daily loss in a portfolio.

For example, a 1:100 chance that $2M can be lost in a day. VAR can be run by the end of each day and communicates a potential loss number to non-technical resources. That’s the good news. The bad news is that VAR cannot be used for all strategies. For example, event-driven strategies cannot use VAR because the act of the event occurring changes the underlying volatility of the stock. In addition, VAR is based on normal distribution and unfortunately long-tail events tend to have clustering effects rather than normal distributions. So VAR doesn’t work great when it is needed most. This calls for other types of risk measures to be used such as scenario stress-testing, P&L volatility, or Drawdown Analysis.

Risk measurement is not risk management. Risk management can be defined as how a fund acts once it has time-sensitive measures. This is where manager risk comes into the equation. For example, does a fund have a separate risk officer or a resource whose duties involve evaluating market risk? Also, risk policies come into play here. Does a fund have defined risk mitigation policies and once thresholds are crossed are exit policies enforced?

Operational risk has been getting increased scrutiny as more institutions have invested in hedge funds and high-profile blow-ups highlight the need for due diligence. Quantifying operational risk requires review of people, process, systems, and data. Interactions between these planes form the operating basis of a fund as a “functioning being”, just as interaction between our internal biological systems form the basis of our existence. I will cover just a few of these interactions in this article.

First off, from a people:process perspective, does a fund act as a business organization with delineation of roles, especially in evaluating risk/return characteristics? Also on the people:process interaction, how would the entity function with the loss of a key resource? With that loss, would the entity be able to recover because of knowledge built within the people:systems interaction.
From a process:systems interaction, what are key measures and how does it manage to these measures.

Finally, from a systems:data perspective, how is the backbone and “central nervous system” protected and can it handle either quick growth or a large loss of either funds or data.
I like to say that operational risk is the only risk without any associated return so it should be getting more scrutiny.