Q:  How would you describe the investment philosophy of your fund? A: We focus on absolute returns and this differs substantially from most mutual funds, which manage money relative to a benchmark. The absolute return strategy aims to produce positive returns, regardless of what the market is doing. Risk is viewed as a loss of capital, not as underperformance to the benchmark. So our philosophy is about producing absolute returns and low volatility and low correlation relative to the broader markets. Q:  Why do you view absolute returns as more important than relative returns? A: It’s not that they’re necessarily more important; it’s really about diversification. Absolute return investing has been used in the past, largely by wealthy families and institutions, as a way to reduce volatility and lower the risk within a portfolio. There are times when the market just doesn’t go up, so people have to diversify into asset classes that don’t correlate well together. This strategy differentiates the portfolio from your other investments and because it tends to have low volatility, it may reduce the risk within an overall portfolio. Q:  And what's your strategy for achieving this objective? A: Our strategy is based on a “manager of managers” approach. We focus on highly skilled, fairly unique managers with sophisticated investment strategies. We have a quantitative approach in selecting the managers, but generally they are managing institutional money, not retail money. That makes the fund rather unique because we’re utilizing institutional level managers and strategies that are not available to most investors. Certainly, there are many hedge funds that have been doing this for a long time, but it hasn't been available to retail investors. It’s fairly new and there aren’t a lot of competitors. So as a part of our offering, we're able to bring this type of institutional investing to the retail marketplace. Currently, we’re working with 13 different managers, who are the sub-advisors for the fund and they’re the ones that actually manage the money. We allocate assets to this group of managers in a wide range of specialized investment strategies. Q:  So the majority of your time goes for selecting the strategies and the allocation, is that correct? A: Yes. We’re using a quantitative process not only to recognize the differences among the strategies, but also to blend the managers and the asset classes together to create a long term return that has less volatility than any single strategy would have. We’re looking for ways to minimize risk factors throughout the portfolio. We're looking at a universe of asset classes and strategies available, whether in the hedge fund world, the mutual fund world, or among separate account managers and we're trying to find the asset classes that over time work best together. It’s not a traditional asset allocation model; we focus more on creating something that has very low correlation across the whole portfolio. Then, within these asset classes and strategies, we're trying to find the managers that have the skill to provide alpha. That’s the key to our process. Q:  Could you describe the asset classes and strategies that you favor in the long run? How do you select them? A: From the variety of asset classes and strategies, the ones that we'd use in our fund are the ones that don’t correlate well together over time. We go back about 15 -20 years and try to piece together these strategies. Then we look for managers that can consistently provide alpha within those strategies. We also look at the correlation they have with their own asset class or benchmark to make sure that they’re getting the returns because of their skill, not because they’re in a certain asset class or strategy. For example, most of our equity strategies are in domestic equities as opposed to international equities, because over time those two asset classes tend to be highly correlated, even when you differentiate between growth and value. And even if the strategies fit from an asset class standpoint, we examine if they have the ability to provide alpha. When we constructed the portfolio originally, we looked at a variety of hedge fund strategies, such as risk and merger arbitrage, convertible arbitrage, etc. We felt that for some of those strategies the alpha was squeezed out because too much money was chasing these ideas. We removed those from the list because we didn’t feel that the alpha was there. Q:  So your performance largely depends upon the selection of strategies and managers who deliver returns on a consistent basis. Could you give us examples of strategies that you have selected? A: Our performance is driven largely by the performance of our managers. At the end of 2005, we had 32% of our assets in market neutral equity, 21% in long/short equity, and 18% in opportunistic long equity as we call it. Those are managers who don’t short stocks, but also don't manage to any benchmarks and look for opportunities wherever they exist. They tend to run fairly concentrated portfolios of 20 25 names and if they can’t find opportunities, they may go to cash. We also have 13% in discretionary fixed income, which is largely total return fixed income, 6% is in hedge convertible, 5% in distress debt, largely high- yield liquid securities, and 5% was unallocated at the end of the quarter. Q:  Why did you choose exactly these strategies? A: We have a quantitative approach. We don't actively manage the portfolio allocation based on any macroeconomic analysis or traditional asset allocation strategy. We believe that investing with skilled money managers is the best way to seek risk-adjusted and low-volatility returns. That being said, our model comes down to looking for the asset classes and then looking for alpha within each asset class. The process involves searching databases based on statistics that show which managers can provide alpha and have very low correlation to their benchmark or asset class. So we’re looking for low beta and consistency in providing alpha within an asset class. Once we have a shortlist of managers that we can talk to, it comes down to whether the manager fits within our objectives. How the managers correlate with the other managers that we may utilize within the portfolio is important. Then we optimize the allocations based on which managers will produce the best risk-adjusted return for the portfolio. All the managers run separate accounts, so we’re not giving our money to a hedge fund or a limited partnership. We’re actually opening up accounts at our custodian, Citigroup, and the money is managed within that sub account. Q:  How many fund managers do you monitor regularly and how often do you change them? A: We’re continually looking for new managers and strategies to improve the optimal mix of the portfolio. We’re trying to be fairly passive with our model once we have it set, but we are looking for strategic or opportunistic changes that we can make going forward. So we’re constantly monitoring our current managers and strategies for style drift, alpha, and beta across the portfolio and relative to various factors. We're monitoring the capacity, the fees or other significant changes, such as a change in a portfolio manager. Across the portfolio, we make sure that there’s not much overlap between managers. We’re pretty happy with the number of managers that we currently have, but we may add strategies as the opportunity arises. Q: What are the prospectus limits in terms of the number of managers or strategies? A: We’ve a maximum of 20% of the assets in a single sub-advisor’s strategy. Currently, we’re allocating to 12 of our managers across the portfolio. These allocations range from few percent up to 15%. When we were building the portfolio, we had a manager with 18.5% allocation because it had a very high investment minimum. For these largely institutional type separate accounts, investment minimums tend to be very high, up to $10 or $15 million. Some of the minimums are higher, but we’ve negotiated those down so that we can use them in our portfolio. Q:  What would lead to a change in the mix of strategies? A: It comes down to risk management because we’re trying to maintain a fairly low beta relative to the overall market. We don’t necessarily benchmark to any index, but we look for an overall portfolio beta of 0.2 or less to the S&P 500, as well as a volatility benchmark of 4% to 6% in terms of standard deviation. This is where we want to be in terms of our portfolio risk management. Anything that may affect the portfolio in terms of beta or volatility, will ultimately change our optimization. There’s a variety of beta factors that we look at, such as the exposure to large-cap or small-cap versus international markets, the exposures to any certain asset class or sector, the single security exposure, etc. Then, if any of the trends in the beta relative to these risk factors is upward, that may be a reason to re-optimize the portfolio. Q:  Who makes this decision? Is it a team or an individual decision? A:We have an investment team that’s made up of four people: myself and the other co-portfolio manager, Alec Petro, along with our two quantitative research analysts. We talk about the portfolio and monitor it on a daily basis. Quarterly, we look at any potential strategic or opportunistic allocation during our investment committee meetings. Monthly, we check if there are any real exposures that we may need to act on immediately. But in terms of the performance of our sub advisors, we hold a more long term view on whether the managers are performing relative to our alpha forecast and expectations. Q:  How do you approach portfolio construction? A: Most of it goes into our quantitative model and we don’t have many traditional qualitative views on the construction, other than certain constraints, such as the allocation limits for single sub-advisor strategies. Then it comes down to a mix of alpha that’s available to us. Our quantitative model takes the track records of those return streams, tries to forecast alpha going forward, and then mixes and matches the strategies in a way that produces the allocations of the portfolio. So the construction really comes down to our selection of sub advisors and once we have those, the model decides how much is given to any one strategy. Q:  Could you describe that model in more detail? A: Because we have diverse sources of alpha, we can’t really maximize return per se, except to select different managers. It's up to the managers to produce return. What we can do is manage the risk. The model attempts to maximize risk-adjusted return or Sharpe Ratio; that's its ultimate goal. We try to improve the Sharpe by attempting to minimize risk and volatility of the overall portfolio through allocation optimization. Q:  So you focus on risk and volatility and the managers focus on returns? A: Well, they are focused on risk as well. One of the selection procedures involves their proven risk-adjusted investment performance and their adaptability to various market conditions. We’re not looking necessarily for the managers that can shoot the lights out, but for those who have a risk-adjusted return focus or an absolute return focus. That's why we examine their performance in a variety of market conditions, such as the bear market in 2002. We're trying to avoid the managers with significant draw-downs when the market does the same. We don’t want the managers that simply behave like the market. As you know, when the market is down 20%, if mutual fund managers lose 15%, they usually consider it a phenomenal year. For us, that would be poor performance. Certainly, we can’t guarantee an absolute return performance, but we can focus on risk-adjusted returns as a primary approach. Q:  What kind of risks do you perceive and how do you monitor them, other than the volatility that you mentioned? A: We are mostly trying to minimize market or systemic risk across the portfolio. That’s where we’re measuring to various risk factors or beta factors. How much risk do we have in our portfolio coming from the overall market? We measure it not just versus S&P beta, but from the small-cap or large-cap segments, or for interest rate risk, to see if there’s any significant beta against those different factors.