Development Of The Strategy Portfolio
    The process for the development of three hedge fund strategy portfolios is similar to the process used to determine the portfolio allocation. As with the total portfolio, a set of criteria is established for each strategy portfolio. The criteria recognize the investor's individual risk tolerance and the availability of funds.
    More specifically:
    no more than 50% of each strategy portfolio can go to a single fund;   
    there must be three funds for each strategy;
    there only can be a 5% chance that the drawdown over the five-year period can be greater than 10%; and
    it is desirable to have greater expected returns for the strategy portfolio than the strategy averages.
    As an example of this process, we will pick the specific funds for the Long/Short Equity Strategy. After the due diligence process there are four remaining candidates. Since only three are allowed for each strategy and no more than 50% can go to any single fund, we use the same process based on best-fit distributions and optimization based on Monte Carlo simulations.
    Figure 10 shows the composition of the Long/Short Portfolio and relevant statistics determined by the optimization process using the 1,000-iteration simulation. The statistics are compared with the Long/Short Equity Strategy assumptions used to create the asset allocation.
    It can be seen that the Hedge Fund Portfolio is consistent with its objectives. It has three hedge funds included and none is greater than 50% of the total Long/Short Strategy Portfolio. There is only a 5% chance that the maximum drawdown over five years will be greater than 10%. We note that the distributions are not normal but do exhibit positive skewness, which means there are more likely to be good surprises than bad. The due diligence process appears to have identified attractive candidates, because the resulting portfolio has a higher expected return than the strategy averages, lower volatility, more positive skewness and much lower than expected drawdowns. Consequently, the implemented asset allocation should have a better chance of meeting or exceeding the investor's objectives.

Conclusions
    In Part I, we showed that the assumption of normality for returns distributions is not valid and that investors may find a more realistic description of risk to be the loss of portfolio assets over any time period in the investment horizon. A loss of 8% in December and an 8% loss in January may seem reasonable if looked at on an annual basis, but an investor would most likely consider a 16% loss over two months to be highly unreasonable. With the use of optimization based on Monte Carlo simulations, a portfolio that is more consistent with a broad range of investor-specific objectives can be developed and evaluated.
    In Part II, we showed how the due diligence process can be incorporated with a quantitative process to select specific hedge funds to use in the portfolio. With the use of best-fit distributions and optimized Monte Carlo simulations, the strategy portfolio can be created. We assumed monthly rebalancing, but multiperiod rebalancing could have been used. More importantly, different rebalancing periods could have been used for the traditional assets and the hedge funds to reflect the lack of liquidity in the funds.
    The process described is more time consuming than throwing historical assumptions into a mean-variance optimizer, but should be more rewarding to the investor and more likely to meet her expectations. Finally, once the Monte Carlo model is built, it can be quickly used to do a wide range of stress testing and what-ifs to insure that the investor thoroughly understands all the implications of the resulting portfolio. 


Eileen Cohen is a portfolio manager in U.S. equities for JP Morgan Fleming Asset Management in New York. William H. Overgard is president of WHO Investment Consulting in Wilton, Conn., and can be reached at (203) 834 2871.

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