Q:  What differentiates you from your peers? A: I think we are unique primarily because of our investment process. Unlike many of our peers, our process is quantitative and objective which requires a unique skill set to build and execute it. Quantitative skills are a must, however, we also have to be patient and persistent because every trading strategy must be thoroughly evaluated qualitatively and then tested using historical market data before it will be implemented. Upon implementation, discipline is the key to avoid emotional trading decisions that can erode profits. We also have high ethical standards in terms of how we manage our business, and we align our personal interests with those of our investors. For example, all of the owners of our firm are required to put at least 50% of their liquid net assets into the funds that we manage. Currently, the three founders of TFS actually have over 100% of their personal liquid assets invested with clients. The founders have invested borrowed money and this speaks both to our confidence and our incentive to add value. In addition, we have voluntarily taken other steps to minimize conflicts of interest and to fulfill our fiduciary duty to shareholders. Specifically, we appointed a board of directors for the mutual fund with a majority of independent members, the owners and portfolio managers are restricted from trading in personal accounts and we have never engaged in soft dollar arrangements with brokerage firms. Lastly, we do believe that our size is a competitive advantage. We are small and nimble and intend to stay that way by closing funds long before we have exhausted the capacity of our trading strategies. Q:  What is your investment philosophy? A: We believe that the best investment decisions are those made objectively with the help of carefully constructed quantitative models. We believe this process will eliminate emotional decision-making and will best capitalize on market inefficiencies. In addition, we think the capital markets are dynamic and therefore a commitment to ongoing research and development is vital to long-term success in this industry. Another part of our philosophy is that we are risk averse. Most of our funds incorporate hedging techniques in an effort to reduce risk. In the case of the TFS Market Neutral Fund, its long positions are hedged by selling a different portfolio of securities short. We believe that hedged products are attractive because of their potential to produce capital appreciation in all market conditions, to lower volatility, and to reduce correlation to other traditional investment classes. Q:  Why is it important to have market neutrality in the fund? A: There are two ways that you can make money in the stock market. One is through general exposure to the stock market, or Beta, and the other is through superior stock selection, or Alpha. Funds with a high Beta, that move in tandem with the overall equity market, are readily available. Unfortunately, they also don’t add much value, or diversification benefit, to most portfolios. Our goal was to create a fund where the majority of the return was in the form of Alpha and that also had a low correlation to other equity investments. To achieve this, we had to greatly reduce the Beta exposure. In doing so, we believed we would create a product that would complement the more common high Beta funds and thereby smooth the portfolio growth curve of the average investor. It’s worth emphasizing that the fund uses a static hedge, meaning that we don’t intend to alter our exposure to the market based on our expectations of the market’s overall performance. There are other long-short funds which, will increase their long exposure or reduce their short exposure in an effort to boost returns. We don’t do that because we believe a static hedge results in more predictable performance across all market conditions and less volatility. We manage the fund to have a slightly positive beta to the market. Q:  What are the key elements of your investment strategy? A: Our investment strategy is based Our investment strategy is based upon bottom-up quantitative models (factor models) that are built using variables that have historically been predictive of future stock performance. The process is very scientific in that we first perform qualitative research on a potential trading strategy. Then, we build historical data that can be used to run a trading simulation on a given model. In other words, we go back in time to simulate how a model would have performed. Though we are quantitative, the variables that drive our models are generally fundamental. We have looked at things such as management changes, earnings quality, and institutional ownership just to name a few. If we can determine through testing that we can produce alpha, then a new variable will enter into our trading logic for both the long and the short side. It’s a dynamic process and we are always validating the existing models and attempting to improve them. Q:  Is your investment approach different for the long and the short side? A: No, we use the same approach for the long and the short side. We read academic studies, journals and articles. We act as scientists and develop a hypothesis of what may, or may not, drive future stock performance. We collect and analyze that data, we challenge the hypothesis and come to a conclusion where we validate or reject the hypothesis. For instance, it’s commonly considered a bullish strategy if a company announces a buyback of its stock shares. We can obtain historical data on all the times that a company has announced a buyback, model it, and try to see if that company has outperformed the market in the first week after its announcement, the first month, the first quarter, the first year, etc. We try to assess the commonly accepted wisdom that that it is a bullish signal. But do the numbers really validate that? As it turns out, we have not been able to validate that strategy. In this case, it seems that conventional wisdom was wrong. Q:  What are the different factor models that you research? A: Over the years, we’ve evaluated dozens of potential systems. A few that come to mind are the buyback strategy mentioned above, management changes, insider trading activity, seasonality, and various earnings related systems such as earnings momentum and quality. Q:  How do you go about a situation where there is not enough coverage of the stock? A: If we are constrained by the data such as is the case on some micro cap companies, we will try to alleviate that constraint by finding other sources of data. If data is simply not available then we just have to exclude the company from our back tests. Q:  How far back in time do you generally go? A: We like to have data going back at least 10 years. Occasionally, we’ll find a proxy for the data or another set of data that is similar, but not necessarily as ideal, that can also be used. In this situation, we may analyze the cleaner data that we have and the proxy to gain additional confidence. Bear in mind that we closely monitor the performance of our models once implemented so we don’t become overly concerned with the data limitations. Q:  Does that mean that any company that has been priced in the last 5 years will be excluded because it hasn’t traded for at least 5 years and thus it doesn’t have the historical data? A: Yes and no. The idea of a simulation is to go back in time to make a trading decision. Our simulation should look at the companies that are available for purchase or sale at a given point in time. So, if a company doesn’t exist 10 years ago then they would be excluded for the simulation during that year. However, they would become a candidate for purchase or sale when they do come into existence. Q:  What variables and factors do you look at for the short side? A: They are similar factor models and just different decision points. The variables are the same, but there may be fundamentally different models. We may treat decreasing earnings momentum differently than we treat increasing earnings momentum. Q:  What are the compelling reasons to incorporate short securities into the portfolio? A: Shorting securities allows an additional opportunity to generate alpha. If we are able to find securities that will underperform the market we will be able to pass more alpha to the underlying investors. In addition, the result in short selling will help to reduce volatility and lower correlation to the broad equity markets. If you simply buy a portfolio of securities it’s very difficult or impossible to create the same dynamics. Q:  Do you follow any benchmark? A: We follow the major equity market indices because we are managing TFSMX to have lower volatility and a low correlation to them. On the alternative fund side, we do not follow any benchmark in particular, but we keep our eye on the CSFB Long-Short Hedge Fund Index. We also watch the Morningstar Long-Short category average. It’s also worth noting that Lipper has broken out long-short equity funds into those with a static hedge like ours and those that have variable exposure. For a true apples-toapples comparison within the market neutral category, Lipper is a good place to look. Q:  In terms of your research process, do you combine technical analysis with the fundamental work? A: No, the factors in our models are fundamental in nature. Everyone sees the term quantitative and thinks technical analysis. That’s just not the case. Q:  How do you go about building your portfolio? A: The models drive the security selection but we have additional constraints. While it is not restricted by the prospectus, we have limited our exposure to any single security to 2% of the fund’s assets, and we have limited our sector exposure to 30%. We are not taking any significant sector bets and we are reducing our individual equity risk by being diversified. As an example, at the end of June 2006 the fund held positions in 295 securities and this number is consistent with the historical average. Q:  How do you break down between the long and short in terms of number of companies? A: Generally, we have more positions on the long side than on the short side. That’s because the fund has a long bias, plus the securities that we sell short generally are more volatile or have a higher beta than those securities that we hold long. A higher beta for the shorts means that it takes fewer to achieve the desired hedge. At the end of June we had almost $23 million long and $15 million short so the ratio of long to short is about 3 to 2. We had about 179 names on the long side, and 116 names on the short side. Q:  When do you decide to sell on the long, or cover on the short, side? A: We will not trim the position just because it has run against us. The decision to close-out a position depends upon why we are holding that position. When new information becomes available, we plug that into our models and if it no longer meets our criteria, we will remove it from the portfolio. We have analyzed various stop-loss techniques in our simulations but have yet to find one that adds additional value. Q:  So if you are holding short and for some reason the stock goes up 50%, you will still hold it? A: Yes, the only reason why we would cover a short is if it no longer meets our criteria. Just because a stock has appreciated doesn’t necessarily mean that it will no longer meet our criteria. That being said, we will trim down our exposure to that stock, because we generally follow the constraint of no more than 2% in any individual equity. If we put on 1.5% and the stock ran against us and it is not 3% of the portfolio, we may trim that down a little.