Editor’s Letter

Current regulatory, economic, and market structure dynamics continue to focus on alternative markets as a primary driver in capital markets. These discussions as to the place of alternative asset classes within the interface of global financial markets focus, in part, on alternative investments providing additional credit to various investment opportunities. Leaving aside the theoretical academic arguments for the relative benefits of various capital flows, in the final analysis, markets rule. In short, when analyzing market activity and its potential impact on investment activity, one needs to follow the traditional adage: “Just follow the money.” In the introductory article “Hedge Fund Investing in the Aftermath of the Crisis: Where Did the Money Go?” Guido Bolliger, Ivan Guidotti, and Florent Pochon investigate the post-crisis preferences of hedge fund investors. They show that after the 2008 crisis, when money started to flow again into hedge funds, investors continued to chase the past best performers. They also find evidence, albeit mixed, that investors sought liquidity, as inflows mainly went into the most liquid funds and strategies. Finally, for single hedge funds, domicile was also a relevant criterion for allocation, with European Union- domiciled funds being the most favored. The authors also find that fee structure had a weak impact on allocation decisions. In that sense, post-crisis money flows were consistent with academic literature and practitioner sentiment that investors’ actions are affected by both recent market performance as well as their current economic condition (e.g., rush to quality).

For most investors, moving in and out of alternative investments is simply not the case of picking up the phone and calling one’s friendly broker. Lockups and various redemption restrictions make external (direct investor) risk management a necessary point of discussion. One reason for reviewing the risk management alternatives for alternative asset investors is that strongly increasing risk often leads to both deteriorating alternative asset values as well as increased client risk aversion to that asset class. For hedge funds, such conditions are likely to trigger hedge fund redemptions that are outside the manager’s control and represent an exogenous event. In an ideal world, hedging the valuation impact of fund outflows on asset valuation would simply involve the purchase of state-dependent securities that pay a nominal amount if an outflow impact occurs and nothing in other states of the world. Alternatively, the risk of fund outflows can be (imperfectly) hedged more directly with various exchange or over-the-counter products. In “Buy-Side Risk Management: Hedging Hedge Fund Outflows,” Steve Satchell and Bernd Scherer develop a model to derive optimal hedging demand and apply it to aggregated hedge fund data.

The ability to manage valuation impacts is, in part, influenced by our ability to measure true value. For many alternative investments, especially those for which market prices are not readily available, performance measurement remains a central concern. In “Venture Capital Fund Performance,” Michael McKenzie and Bill Janeway analyze the investment performance of a large database of venture capital (VC) funds sourced from two limited partners. The results suggest that a portfolio of VC partnerships can provide an average return that is superior to the public equity market, although individual fund returns are highly positively skewed. Absent these outliers, the level of fund performance is more in line with public equity market returns. This article also provides some preliminary evidence of VC fund performance during and immediately following the dot-com bubble.

Similarly, for other assets for which direct investment entails valuation and liquidity impacts, the question remains whether market alternatives exist that may provide some risk-return benefit while reducing some trading and valuation risks. For example, insurance-linked securities (ILS) are seen as a source of alternative beta. From an investor’s point of view, this suggests a natural question: Besides being described, analyzed, and modeled, can the ILS risk premium be systematically captured and replicated? In “Insurance- Linked Securities (ILS): How to Construct a Performance Index,” Lars Jaeger, Ivan Melnychuk and Samuel Scherling offer a methodology for the construction of a performance index designed to cost-efficiently capture ILS alternative beta. They discuss some implications of the availability of ILS performance indices for both passive and active management of ILS exposures.

Many of the questions we ask are, of course, dependent on the knowledge we have. For example, in the private equity and real estate area, research often is restricted to quarterly data. For hedge funds, monthly data remain the dominant reporting interval. The academic research on hedge funds that is based on qualitative data (fees, redemption restrictions) from the date of the most current database download, while performance data are historical, assumes that changes in qualitative data over time are minimal. Similarly, investors should remember that hedge fund databases were created and grew at different times. Thus, large differences in the number of managers reporting as well as differences in other fund platform characteristics may exist between various hedge fund databases. If these databases contained enough manager breadth and depth, results at the portfolio level could be similar across various databases; however, differences may still exist at the average manager level, especially for small subsets of analyses (e.g., strategy, fee level, etc.). In “Hedge Fund Database 'Deconstruction’: Are Hedge Fund Databases Half Full or Half Empty?” Thomas Schneeweis, Hossein Kazemi, and Edward Szado compare performance characteristics of two major databases often used in hedge fund analysis (CSFB/Tremont and CISDM).More specifically, they compare performance results at the strategy level for 1) all reporting funds,2) funds denominated only in U.S. dollars, and 3) a cleaned set of funds with duplicates removed (e.g., multiple share classes or currencies).Results show some return and risk differences between the two databases at the portfolio and average manager levels. These differences, however, are often relatively small. In the end, the impact of database usage and the necessity of “deconstructing” one’s database depends, in part, on whether one views the glass as half full or half empty.

If issues exist on measuring and monitoring hedge funds, for more esoteric assets, the issues surrounding performance measurement may be of even greater importance. Different art objects are likely to be priced by means of different systems of hedonic characteristics; more precisely, different evaluation procedures for high- and low-price items are often postulated. However, the empirical evidence on this point is scant. The purpose of “The ‘Right’ Price for Art Collectibles: A Quantile Hedonic Regression Investigation of Picasso Paintings” is to fill this gap with a quantile hedonic regression approach. Using a dataset of 716 Picasso paintings sold at auction worldwide, Antonello Scorcu and Roberto Zanola highlight the critical role of different price classes in determining the evaluation criteria of art items.

In our last section, we continue to offer our readers a practitioner’s perspective on several of the issues (liquidity, investment restrictions) raised in the previous articles. In “The Four Agreements of Terms and Conditions: Lockups and Transparency,” Eric Hirschberg postulates a framework for aligning interests between investors and managers with respect to liquidity terms, performance compensation, and transparency by the application of terms and conditions.

The issues raised in the above articles invite a sense of déjà vu—been there, seen that, done that. One might think, or at least hope, that these issues might have already have settled in the pages of The Journal of Alternative Investments. Regulatory, economic, and technological conditions change, however, and the impact of these changes on market conditions requires constant review. In addition, we are constantly getting better data, as well as a better understanding of historical data. In short, our understanding of the very dynamics of academic and practitioner research varies, which should shock no one. Again, I remind our readers that if it were easy, they would hire a monkey and feed it bananas.

I continue to look forward to your comments and submissions, which help us to manage the change.

Thomas Schneeweis

Editor

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