As financial markets continue their slow ascent to normalcy, we are reminded of the debate in any area of analysis of “what is normal?” One of the primary advances in finance over the past decade is the increased emphasis on the conditionality of market activity. The fact that market activity, as well as the corresponding asset and market risk, is conditional on such a range of factors, that any definitive model of market risk and return may be regarded as unattainable, leads both practitioners and academics to attempt to find a set of workable models of asset and market behavior which is both more simplistic than the true underlying process as well as more complex than simple “one size fits all” approaches to market behavior and risk and return estimation. Moreover, given the changing nature of financial markets those models that are often perceived as normal themselves require constant review. Nowhere is this more true than in the debate surrounding various approaches to asset allocation as well as the means to manage risk within an asset allocation framework.
In the first section on Asset Allocation, the articles emphasize both the multi-factor nature of risk estimation as well as the unique portfolio concerns of investors with large non-tradable asset positions. Both of the articles offer a more complex analysis and approach to the risk and return opportunities facing investors. In contrast, the articles in the section on Risk Measurement and Management focus on more common or traditional approaches to viewing investment risk (leverage and inflation) in the context of two traditional alternative investment strategies (hedge funds and commodities). Each of the articles in the first two sections (Asset Allocation and Risk Management) attempted to address issues that reflected some of the impacts of the conditional nature of asset markets. One of those conditional factors is of course changing regulatory impacts. Over the past several years, the impact of the financial crash in fall 2008 has led to a number of actual as well as proposed regulatory changes. Restrictions on short sales are indicative of regulatory actions to impact market activity. In the section on Regulation, we provide an additional view on the potential impact of short sale restrictions on the performance of various asset classes as well as unique strategies. Results show that while a single answer is not evident as to the benefits or costs of short sales, there is little evidence of a simple positive market response to a lower level of market and strategy risk.
In the final section on Perspectives we move away from the more modern alternative strategies and the more traditional approaches to risk and return analysis. The first article addresses one of the more traditional areas of alternative investment (art investment) and the dynamics impacting the changing demand for specific areas of the art market. The dynamics of changing markets as well as changing forms of potential investment are also the focus of the last article. Today, investors have a range of investment opportunities to capture the return and risk characteristics of various investment strategies. Even within a particular limited strategy approach (e.g., investment strategy investment trackers) there exist a range of approaches. The range of approaches is due not only to various underlying assumptions as to the most suitable means to capture the return and risk characteristics of a corresponding benchmark but also to changes in the underlying structure of the market over time that changes the availability of various underlying investments.
ASSET ALLOCATION
In “The StressVaR: A New Risk Concept for Extreme Risk and Fund Allocation,”Cyril Coste, Raphaël Douady, and Ilija I. Zovko introduce a novel approach to risk estimation based on nonlinear factor–models—the “StressVaR”(SVaR). Developed to evaluate the risk of hedge funds, the SvaR appears to be applicable to a wide range of investments. The computation of the StressVaR is a three-step procedure whose main component is to use the fairly short and sparse history of the hedge fund returns to identify relevant risk factors among a very broad set of possible risk sources. This risk profile is obtained by calibrating a polymodel, which is a collection of nonlinear single-factor models, as opposed to a single multi-factor model. The authors then use the risk profile and the very long and rich history of the factors to assess the possible impact of known past crises on the funds, unveiling their hidden risks and so-called “black swans.”
Given recent interest in the activities of sovereign wealth funds (SWF), “Portfolio Choice for Oil-Based Sovereign Wealth Funds” reviews the financial economics of portfolio choice for oil based investors. Bernd Scherer views the optimal asset allocation problem of a sovereign wealth fund as the decision making problem of an investor with non-tradable endowed wealth (oil reserves). Optimal portfolios combine speculative demand (optimal growth) as well as hedging demand (hedging resource fluctuation risk) and their level of risk taking should depend both on the fraction of financial wealth to resource wealth as well as the oil shock hedging properties of its investments. As an additional factor, the author introduces background risk for a SWF in the form of oil reserve uncertainty. SWF with large uncertainty about the size of their reserves should invest less aggressively and vice versa. The article also identifies the optimal speed of the extraction policy (oil to equity transformation) as a driving force for portfolio adjustments across time and presents a dynamic programming approach to approximate portfolio adjustments.
RISK MEASUREMENT AND MANAGEMENT
Average leverage is often used as a measure of risk. However, average leverage in a limited liability context should not be computed as a simple arithmetic average of the underlying constituents. In fact, using a simple arithmetic average can give misleading results. For example, the simple arithmetic average leverage may give results which run counter to the actual risk exposure for certain portfolios. In “Limited Liability Leverage (L 3):A New Measure of Leverage,” Philippe Jorion and Mayer Cherem introduce a new measure (L 3) which corrects the simple average for the limited liability framework. This new measure is discussed in the context of a portfolio of hedge funds and compared to a multi-strategy hedge fund structure, where trading units do not have limited liability. This perspective can also be extended to reflect the lower risk of a financial system with many small institutions relative to a system with large, “too big-to-fail” institutions.
In “Protection Potential of Commodity Hedge Funds,” Pierre Jeanneret, Pierre Monnin, and Stefan Scholz show that investing in a portfolio of commodity hedge funds yields higher returns and a better control of downside risk than investing in long-only commodity indices. They also show that, contrary to a widespread belief, long-only commodity indices do not necessarily provide an efficient inflation hedge during periods of high inflation and may induce a cost in low inflation periods. Commodity hedge funds do not provide a better hedge in periods of high inflation but they do not bear any cost in low inflation periods.
REGULATION
In “Spillover Effects of Counter-Cyclical Market Regulation: Evidence from the 2008 Ban on Short Sales,” Abraham Lioui looks at the impact of the ban on broad market indices in the U.S. and in Europe (the United Kingdom, France, and Germany). Since these indices and their performance are of great concern to the asset management and hedge fund industries, it is important for practitioners and policy makers to understand the impact of changing the rules of the game (banning short sales) on the return distribution of these indices and to assess the potential spillover effects of a counter-cyclical regulation affecting only one segment of the financial market. Lioui examines the ban on a broad range of market and strategy risk factors and shows that while the ban may be responsible for a substantial increase in market volatility, its impact on higher moments of index returns is not systematic (skewness and kurtosis of the return distribution of only a few indices were affected) or robust (using some robust measures of higher moments makes the impact of the ban disappear).
PERSPECTIVES
Art and art investment has often been motivated both by the availability of certain art forms as well as the changing nature of the source of demand due to changes in specific sources of wealth. Luc Renneboog and Christophe Spaenjers investigate the investment performance of modern Russian art. In “The Iconic Boom in Modern Russian Art,” a hedonic analysis of more than 50,000 art transactions results in a geometric average return of 3.97%, in real USD terms, between 1967 and 2007. The Russian art index shows an impressive annualized return of 12.37% since 1997. This is roughly double the average yearly appreciation of a global art market index over the same period. Art from the nineteenth century has performed especially well. The returns on Russian art correlate positively with the returns on global equities, gold, and (especially) London real estate. Also, they seem to be affected more by trends in oil prices than are global art prices. The results illustrate how the new wealth created in fast-developing economies has an impact on the demand for art from these countries, which reflects a home bias in taste.
In recent years, there has been a dramatic increase in the number of systematic algorithmic products that attempt to capture the risk and return of a particular asset class or fund strategy. These products may be stand-alone investments created to provide direct “replication” (e.g., almost identical securities) as a comparison benchmark or they may be constructed expressly to “track” (e.g., similar but not identical securities) an existing non-investable or investable benchmark. Various approaches exist in the creation of these tracker products. In “Asset Class and Strategy Investment Tracking Based Approaches,” Garry B.Crowder, Hossein Kazemi, and Thomas Schneeweis review alternative approaches to the creation of investment trackers. In this article, the authors concentrate on the underlying rationale for fund tracker products, the alternative approaches often employed to create such products, and practical concerns related to strategy or fund tracking based products. They also provide a brief review of the performance of existing tracker products as well as examples of tracker products use in multi-asset allocation.
In summary, things change, and the more they change the more investors are required to assess the impact of those changes on traditional approaches to asset return and risk management. While changing market conditions, regulatory actions, and investor perceptions may result in both practitioners and academics being required to change some of their own fundamental beliefs, we must remember that change is good. Without change, with constant answers to unchanging conditions, they could simply hire a monkey and feed it bananas.
As we move beyond the “new normal,” we look forward to the constant dialogue as the impact of the ever changing market.
TOPIC: Real assets/alternative investments/private equity
Thomas Schneeweis
Editor
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