Charles J. Gradante October 1998


The high returns attained by well known hedge fund managers such as George Soros have attracted the attention of investors enamored by the 20%, 30%, 50% returns, as well as, the ever so often reported 100% returns attained by "macro" hedge fund managers. What is even more disconcerting, is a 1998 study by Montgomery Securities that revealed investors expect macro managers to return over 30% annually. As astonishing as these expectations may be, these fund managers and their returns are not indicative of the hedge fund industry as a whole. The question remains "can the risks in hedge funds be quantified given their unique nature?" Value-at-Risk (VAR) is widely accepted by the financial markets as a risk measurement standard. It is a model acclaimed for its ability to measure risk across different financial instruments. After careful examination of the underlying assumptions used to calculate VAR and the characteristics of hedge funds, we have concluded that VAR may not be the appropriate risk measurement model to employ for all hedge funds. This report will highlight some of the pitfalls of VAR when used to measure hedge fund risk. Value-at-Risk was employed by Long-Term Capital Management (LTCM); clearly it did not work…but why?


Hedge funds are private investment partnerships within the "alternative investment" asset class. The investment manager typically has market skills, career experience and a track record that is exemplary and often unique. Hedge funds are similar to mutual funds in that they are actively managed investment "pools" of capital holding positions in publicly traded securities. They differ from mutual funds in their investment and trading strategies, use of a broad range of securities, high performance criteria, and risk/return objectives. Hedge funds often seek to invest in more complex markets, riskier securities and pursue more aggressive investment or trading strategies. Because of this flexibility to invest in a variety of markets, hedge fund managers may not seek to outperform a benchmark, such as the S&P 500 Index, but rather they seek to exploit mis-pricing in the global financial markets.

Originally hedge funds were established as investment vehicles that attempted to hedge market risk in the portfolio. A common strategy would be to buy long positions in undervalued securities and simultaneously sell short positions in overvalued securities, thus creating a "hedged" position. The result is an effective "bet" that the long position will appreciate while the short position did nothing in bull markets; but more than offset losses in the long position in bear markets. This long and short stock selection, when executed properly, hedges out market risk.

Hedge funds tend to employ dynamic trading strategies. A dynamic trading strategy may utilize any combination of the following: leverage; concentration; market timing and market trending strategies; short selling of securities; event driven; and convergence or divergence between two or more securities.

Modern portfolio theory indicates that: (a) investors should be compensated for risk and; (b) asset diversification reduces portfolio volatility or risk.1 Hedge funds offer both of these advantages to investors. Investors have the ability to add riskier, and therefore higher returning assets to a portfolio while, at the same time, reducing the volatility or risk of their portfolio.


Over the last several years risk management has become the focus of financial markets participants. Risk management is the process of identifying and managing potential risks an entity faces during the course of business. Although the main impetus of risk management began with banks looking at risk in their own portfolios, risk management has expanded to other parts of the financial industry. Now investment managers are being required to explain investment strategies, demystify their models, and become more open about their portfolio risks.

There are several motivations behind the push for transparency of risk exposures. First, are the incidences of billion dollar losses stemming from risk management negligence by several financial entities. The most notable is the $ 1.5 billion dollar loss sustained by the Orange County Investment Pool in December 1994.2 In 1998, Long-Term Capital Management [LTCM] lost almost $3 billion of investor capital. Public attention and debates of these incidences have made individual investors more sophisticated about the numerous risks inherent in financial markets.3 Second, regulators of financial markets have addressed the issue of risk measurement and have made full disclosure mandatory in some public sectors. Third, and perhaps most important, the flow of institutional money into hedge funds is growing at a steady pace. Pension funds are allocating more money to hedge funds. They are also required by law to have sufficient knowledge of the risk exposure incurred by their portfolios. Hedge funds have been scrutinized by Congress. Disclosure by hedge funds to their creditors and partners was at the heart of the 1998 Congressional Hearings regarding LTCM and the hedge fund industry.

The Securities and Exchange Commission (SEC), Bank for International Settlements, and the Global Derivatives Study Group are among financial market regulators and study groups which have developed and recommended risk management standards and policies, as well as, procedures for risk measurement. One quantitative model that has received numerous endorsements from the financial markets industry to address risk measurement and support risk management mandates is Value-at-Risk.

Value-at-Risk (VAR) is a method of measuring the financial risk of a portfolio over some specified time period. It provides a consistent approach to valuing asset exposures using probability analysis based upon a consistent confidence level and time horizon4. VAR is a rather simple model to manipulate but is extremely dependent on the assumptions and methodology used. It offers an adequate approximation of how much a portfolio or firm could lose from changes in the prices of assets it holds5. Numerous industry participants have found VAR extremely useful in analyzing their business and market risks. Mutual fund managers have incorporated VAR into their risk management process and disclose this information to investors. An in depth study of the practicality of hedge fund managers using VAR to measure their market risk exposures is beyond the scope of this paper. Instead, we will examine the usefulness of a VAR calculation to an investor who is evaluating and comparing hedge funds. This paper will also evaluate the accuracy of this risk approximation when combined with a traditional portfolio of stocks and bonds.


VAR is an estimate of the expected maximum loss over a target time horizon within a given confidence level under assumed market conditions. Introduced in 1993, among the reasons VAR has gained popularity is its ability in measure risk across different financial instruments. In general, it can be used to calculate risks implicit in price movements for equities, commodities, bonds and currency exposures provided there is sufficient data on assets and risk factors from which to calculate the probabilities and correlations of future price changes. VAR can capture the combined effect of a portfolio's underlying volatility and its exposure to market risks. VAR is a forward looking market risk indicator.

A VAR calculation is dependent upon the selection of two quantitative factors: the length of the risk horizon and the confidence level desired. The target risk horizon is the length of time a manager needs to evaluate risk exposure. For instance, a manager can calculate risk exposure over a daily, monthly, or quarterly time interval. The proper selection of a risk horizon varies among industry users and is related to performance evaluation, trading strategies, and the liquidity of securities within a portfolio. The confidence level is the degree of confidence that one can place that a loss will not exceed the VAR indication. For instance, at a 95% confidence level, a manager can expect (based on historical probabilities) to lose no more than the VAR measure 95% of the time over the risk horizon.

Once the risk horizon and confidence level are selected an investment manager must generate a probability distribution of possible changes in the portfolio value over the risk horizon. Price and return distributions for each security is generated. These distributions represent the price or returns for each security over the risk horizon. Therefore, the "value at risk" of a portfolio is the dollar loss corresponding to a pre-defined probability or "confidence level." Here in lies the "achilles heel" of value-at-risk modeling.


In general, some VAR models are based upon several key assumptions6: (a) returns are, in statistical terms, normally distributed; (b) markets are liquid; (c) historical and current market price data are available; (d) correlation data are either available or easily calculated from historical or current market data; (e) securities and portfolios are static over the risk horizon. Based upon these assumptions, VAR is not an appropriate risk measurement model for most hedge fund managers to employ.

VAR calculations assume that portfolio assets and risk/return profiles are static over the time horizon. Volatilities in illiquid and inefficient markets, such as emerging markets, may prove difficult to model using VAR. There may be very little historical data and risk profiles may change over time making price returns difficult to forecast. Losses in these markets can be steep and sudden. The Asian crisis is a perfect example. Inaccurate information about debt exposures companies had on their balance sheets led to inaccurate market valuations. Asian stock markets lost over 50 percent of their original value and currencies were devalued by more than 50 percent by the end of 1997. Asia's risk profile and volatility changed literally overnight. "One off" events, such as the Russian debacle in August 1998 can also position the VAR approach ineffective.

Some hedge funds employ market or event driven strategies. These strategies perform well when the market is adversely affected, as they did in the stock market crash of 1987. VAR calculates the expected maximum loss over a target time horizon within a given confidence level under "assumed" market conditions. Turning the market upside down we can assert that a hedge fund that follows a market event driven strategy is safe in adverse market conditions. A traditional mutual fund performs well during normal market conditions and most event driven strategies perform well during abnormal market conditions. Different assumptions must be made to properly calculate a VAR for both of these strategies. However, once the hedge fund's risk measure is calculated: (a) how comparable is this number to other VARs; and (b) how can an investor incorporate this measure into their traditional portfolio VAR? Can these numbers be combined to formulate a total VAR for an investor's portfolio?

To complete the story on risk measurement, there are a number of risks in the financial markets that can not be captured in VAR or any quantitative model. Most notable for hedge funds are liquidity risk, political risk, model risk, and technology risk. Long-Term Capital VAR models were ineffective because of extremes that occurred in each of these areas, particularly August 1998.


Risk management is a process meant to engage investment managers and investors in the constant evaluation of risk/reward performance. A risk management model is only one aspect of this process. Value-at-Risk is a summary statistic that quantifies the exposure of an asset (or portfolio of assets) to risk; or the risk that a position declines in value with adverse market price changes. It is a powerful technique that has improved the evaluation and understanding of market risk, but it is an expectation of outcomes based on specific assumptions. VAR, depending on its assumptions, may be difficult to implement on complex asset return characteristics and dynamic investment strategies employed by hedge fund managers, especially macro managers and managers using illiquid securities and illiquid derivatives. VAR is more accurate in traditional liquid markets, however, hedge funds tend to invest in illiquid and complex markets. Conclusively, VAR did not work for Long-Term Capital Management nor Orange County. It did nothing to prevent massive portfolio losses during the Asian crisis and the Russian debacle. At best, VAR is a rear-view mirror approach future risks.

Hedge funds are a unique asset class that has received attention for their impressive returns. The risks, however, can be equally striking. These returns must not enamor investors. Investors should seek hedge funds that provide the necessary risk and return objectives that complement their traditional assets. Great care must be taken to fully explore and quantify risk. To complement any risk measurement model, it is strongly suggested that investors perform in-depth due diligence on a case-by-case basis. Individual investors may also want to seek hedge fund advisors who have experience in analyzing hedge fund risk/reward components.

1 Asset diversification reduces risk because all securities and markets are not correlated; that is, different markets and security classes react differently to changes in market conditions. Securities can either move in opposite directions or at a different pace to be not correlated to each other.

2 For a detailed discussion of Orange County Investment Pool loss see for example, Philippe Jorion, "Lessons From the Orange County Bankruptcy", Journal of Derivatives Vol. 4, No. 4 (Summer 1997): pp 61-66.

3 There are a number of articles and books that address and fully explain the derivative losses of 1993 - 1995 (Proctor & Gamble, Barings PLC, and Orange County).

4 Although there is quite a bit of literature on VAR for a general description, see Philippe Jorion, Value at Risk (Chicago: Irwin Professional Publishing, 1997)

5 We are using a very simple explanation of VAR for the purposes of this paper. There are three different VAR models that use different assumptions and methods for calculating risk measures. For a more in depth explanation see for example Tanya Styblo Beder, "Report Card on Value at Risk: High Potential but Slow Starter", Bank Accounting & Finance.

6 As previously stated for more a more in-depth discussion of VAR models and assumptions see for example Tanya Styblo Beder, "VAR: Seductive but Dangerous" Financial Analysts Journal: September/October 1995: 12-24.



© 2007 Hennessee Group LLC, All Rights Reserved.