The Financialization of Commodity Markets

Investing During Times of Transition

A. Zaremba, Kenneth A. Loparo

• Publisher: Palgrave Macmillan
• Year: 2015
• ISBN:
  9781137476395
• Topic: Business
• Subtopic: Business General
• Index: Business

The landscape of commodity markets has drastically changed in recent years. Once a market of refineries and mines, it has become the market of investment funds and commodity trading advisors. Given this transformation, are commodity investments still as beneficial as 20 or 30 years ago? This book is an attempt to answer these questions.

Chapter One

Asset Allocation in Commodity Markets

The focus of this book is strategic asset allocation in commodity markets in relation to the phenomenon of financialization, which is the growing importance of financial investors to these markets. Terms such as asset class, strategic allocation, and even commodities, are not unambiguously understood in existing literature on the subject. The aim of this chapter is to clarify the key issues discussed in the book. In the first place, we will discuss and understand the classes of investment assets; next, we will define strategic asset allocation; and finally, we will propose methods aimed at gaining exposure to commodity markets and examine their importance to this study.

Classes of the Investment Assets

There is no strict definition of asset classes, nor is there any closed list of these assets (Idzorek 2007). Asset class can be understood very broadly or very narrowly, depending on the chosen convention and needs. A general definition suggested by Greer (1997) is, “An asset class is a set of assets that bear some fundamental economic similarities to each other, and have characteristics that make them distinct from other assets that are not part of that class.”

The concept of asset classes is important to financial market practitioners for several reasons, as indicated by, for example, Scherer and He (2008). First, strictly defined investment asset classes make decision making in the top-down¹ processes easier. Considering the fact that asset classes share the same characteristics, they should respond to changes in external factors and the impact of economic forces in the same way. Second, definitions of asset classes streamline and facilitate the construction of a portfolio with various optimization models, the operation of which is based on a risk-return relationship. This is because most of the optimization models react to significant changes in the optimal weight of each asset, in response to small changes in the characteristics of those assets. In other words, optimization models tend to potentiate the errors in estimates in portfolio optimization. For example, if two instruments, X and Y, have a risk and correlation almost equal to that of other instruments but instrument X has a somewhat higher expected return, the optimization model will usually allocate to it a significantly larger part of the portfolio, despite the fact that X and Y are very similar to each other. Both instruments are treated by the model as substitutes even though, by definition, different classes of assets are not substitutes. The third reason is related to the specifics of the operation of the investment industry, where there is always an ongoing search for new asset classes. On the one hand, new asset classes hold the promise of greater diversification for the clients of investment firms, while on the other hand, they give investment fund managers the opportunity to offer new products. In summary, the definitions of asset classes not only streamline and simplify the management process, but also have a measurable impact on business processes in the funds industry.

The catalog of asset classes divided into the most capacious groups was suggested by Greer (1997). He defined three super asset classes: capital assets, assets that are used as inputs to creating economic value, and store of value assets.

Capital assets are defined by their related right to utilize future cash flows. The value of capital assets is assessed by the present value of their future cash flows to the owner.

According to the Modigliani–Miller theorem, the value of a firm is unaffected by how that firm is financed, but it is affected by future cash flows.² The way they are distributed among the shareholders and creditors is a secondary issue, which is irrelevant to the value of a firm (Modigliani and Miller 1958). Thus, stocks and bonds are typical examples of capital assets. In addition to the above, this superclass also includes hedge funds, private equity funds, and credit derivatives (Anson 2009).

Assets used as inputs to creating economic value are those that are consumed or converted to other assets in the production cycle. This superclass includes, above all, the so-called physical resources: grains, metals, energy raw materials, and livestock. Assets used as inputs for creating economic value cannot be valuated based on the present value of future cash flows, because they do not generate cash flows.

A good example of assets used as a store of value is art (Anson 2009). A picture cannot be transformed in the production process, nor will it be followed by any future cash flow. Its monetary value can be seen only through a sale—or some other form—of transfer of ownership. In addition to art, the class of assets used as a store of value typically includes gold and other ores, although it is worth mentioning here that the border between the asset classes is quite fluid, because ores can also be used in the production process.

Other authors adopt narrower definitions of asset classes that are, at the same time, more consistent with common practice. Anson (2009) pointed out that, historically, four asset classes were distinguished: stocks, bonds, cash, and real estate, which were further divided into subclasses such as large companies, small companies, and foreign companies, for example. Anson has suggested extending this division by five alternative asset classes: commodities, hedge funds, private equity funds, futures funds, and credit derivatives. Sometimes, assets are classified based on risk factors or exposure to risk; these are credit spreads and interest rates (Idzorek 2007).

The method of defining and testing the distinctness of the asset class is a complex topic in existing literature. Market practitioners usually refer to the low correlation with other instruments on the market. However, this definition seems to be insufficient. If it was, even a draw ticket bought in a lottery could be defined as a separate asset class because, by assumption, it has zero correlation with the behavior of the stock and bond markets; although, as a rule, no reasonable investor should invest even a fraction of his assets into draw tickets.

A formal interpretation of the class of assets is as follows (Greer 1997): each potentially distinct asset class i with return of R_i bearing a risk premium above the return on money market c, which cannot be explained by other j = 1, 2, . . . , J existing asset classes bearing a risk premium R_j−c can be perceived as a distinct asset class.

A formal interpretation of an asset class is offered by Greer (1997). According to this author, each potentially distinct asset class with excess returns over risk-free rate, which cannot be explained by excess returns on other existing asset classes, can be perceived as a truly distinct asset class.

By illustrating this theorem with an example given by Scherer and He (2008), we should assume that there is a potentially distinct asset class that consists of 25 percent of stocks, 25 percent of bonds, and 50 percent of cash; its annual standard deviation is 30 percent and its expected risk premium is 1.5 percent. In the same market, there are stocks and bonds, the expected returns on which are 5 percent and 2 percent respectively, with volatility being 15 percent and 5 percent respectively. Considering the content of a new asset class, it can be calculated that its correlation with stocks is 0.24. Nevertheless, despite the low correlation with other asset classes and the positive risk premium, we cannot conclude that this instrument constitutes a distinct asset class. A typical optimization model would not allocate in it, because a portfolio with better profit, risk values, and Pareto parameters than those of the possible new asset class being discussed can be constructed based on the instruments already existing in the market. All investment portfolios that can be created with the “new” asset class can also be constructed with existing instruments. The growing investment universe does not move the efficient frontier upward, nor to the left, as the asset class does not generate a return directly related to its specific risk. If there was such a premium, and if the efficient frontier was significantly moved upward and to the left, then we could speak of a distinct investment asset class allowing the construction of a portfolio with better parameters in terms of its risk-return relationship.

The empirical study in the latter part of this book bases on the four asset classes. Two of them are a reference point for the traditional investor, whose investment portfolio usually consists of stocks and bonds. The other two are placed under analysis. These are the passive investment strategies implemented in commodity markets—for which a relevant benchmark tracking its nature is based on the commodity market indices—and the active investment strategies in commodity markets—for which managed futures are a representative measure. Such an approach is widely accepted and has been used in many studies (Lintner 1983; Scherer and He 2008; Anson 2009; CISDM 2009, etc.).

Strategic and Tactical Asset Allocation

In financial literature, there are three types of asset allocation: strategic asset allocation, tactical asset allocation, and benchmark asset allocation.³ In any case, the aim is to construct a portfolio with possibly the best risk-return relationship profile (Fuss, Kaiser, Rehkugler, and Butina 2006).

Strategic asset allocation is based on long-term—usually at least five-year—forecasts for each asset class. Long-term forecasts, by nature, are not normally updated, so strategic allocation is characterized by weights that are stable over long term. Strategic allocation can be expressed as a specific percentage of the portfolio (e.g., 25 percent), but it is often formulated also as a range within which some variations are acceptable (e.g. 20–30 percent).

Tactical asset allocation is based on short-term deviations from the strategic objectives, acceptable in order to take advantage of the current market situation. Tactical allocation is usually much more dynamic, as compared to the strategic one, and the investment horizon associated with the decision-making usually ranges from one month to three months.

As for benchmark allocation, the manager invests the resources according to the weights defined in the established benchmark. This approach applies, for example, to index funds and funds adopting quasi-index strategies, such as enhanced-indexing (Ruh 2001; Kommer 2007; Magers 2007).

Benchmark allocation is done with the a priori defined asset weights within a given benchmark, and it does not require any forecast from the fund manager. Strategic allocation relies mostly upon historical data (average rate of return, standard deviation) as a basis for the forecasts of the next five years. Such an approach is dangerous because it implies that no other information is relevant to the strategic allocation. On the other hand, tactical allocation is the result of active and dynamic forecasts, made by a fund manager, based on various premises.

The study in the last part of the book focuses on the issue of strategic asset allocation. In this author’s opinion, it is possible that the structural changes that have occurred in recent years in the commodity markets might have a significant impact on the premises for formulating the strategic asset allocation. One of the potential consequences of financialization of the commodity markets may be the fact that including commodities into the process of strategic allocation is currently unfounded.

Investments in Commodity Markets

The asset class and the way to gain exposure to this class have to be distinguished between when selecting investment assets. For example, in case of stocks, the exposition to them can be gained, inter alia, through the direct purchase of stocks, through acquisition of participation units in an equity fund, or by adopting a long position in index futures. Unlike most asset classes for which exposure can be achieved in a relatively clear and simple manner, the situation is quite different in the case of commodities. There are three basic ways to obtain exposure to the market of commodities, each of which results in different profiles of risk and revenue (Idzorek 2007):

• direct purchase of physical commodities,

• portfolio of companies related with commodities,

• commodity futures.

Investments in physical commodities are not widely used (Idzorek 2007). Most of the commodities are consumed and decaying, particularly, agricultural commodities and livestock. The only exceptions were ores; thus, apart from funds investing in gold or silver, for example, there are only a few funds and investors allocating their resources through direct purchase of commodities.

Using commodity companies as a proxy for commodities as an asset class is a highly controversial issue. This investment gives exposure to the skills and competencies of the boards of management of companies and their business lines, and, in fact, it is a subclass of a broader class of assets; namely, the stocks rather than the commodities themselves. What’s more, many companies may hedge their positions in the commodity markets with hedging strategies. As a result, the commodity companies are usually much more correlated with the stock market than with the commodities market (Zaremba 2011d). Some interesting research on this subject has been accomplished by Gorton and Rouwenhorst (2006). The authors had built up a portfolio of commodity companies according to the SIC codes, and studied its behavior for 41 years. The correlation of the portfolio with the index of commodity futures was 0.4, and its correlation with the stock market was 0.57. In other words, the behavior of commodity companies is more similar to companies on a stock market than those in a commodities market. What’s more, historically, the commodity companies bore lower rates of return than commodity futures; however, it is not definitely demonstrated that they effectively hedge against inflation. As a result, we cannot assume that the portfolio of commodity companies is a good way to gain exposure to the commodities market (Baierl, Cummisford, and Riepe 1999; Chen and Pinsky 2003; Idzorek 2007).

The third method to gain exposure to the commodities market is by investing through futures contracts. In this case, there are two ways to gain exposure to commodity futures markets: “passive investment strategies” through a basket of commodities that compose the index or the sub-index; or “active investment strategies” through managed futures.⁴

The index investment consists in opening a position in a basket of futures that is composed of an index or sub-index, and, then, they are systematically rolled at the time of expiration of each contract. Such a basket is fully hedged with secure instruments—most often with treasury bonds—and the gained returns are associated with a few different sources of profit, including changing prices in the spot market, profit from rolling positions, and interest from a margin deposit.

The literature on the subject points to a number of properties of investments in commodities with indices of commodity markets, which are attractive from the investor’s perspective. We should mention here the right-skewedness of the distribution of return rates (Deaton and Laroque 1992; Armstead and Venkatraman 2007); regression of rates of return toward the mean (Sorensen 2002); positive correlation with inflation (Bodie 1983; Froot 1995; Till and Eagleeye 2003a,b; Gorton and Rouwenhorst 2006; Akey 2007); positive correlation with economic activity (Strongin and Petch 1995; Strongin and Petch 1996; Gorton and Rouwenhorst 2006; Armstead and Venkatraman 2007; Kat and Oomen 2007a,b; Adams, Fuss, and Kaiser 2008); long-term positive risk premium (Till 2007a, b,c); and incomp...

Table of contents

• Cover
• Title
• 1  Asset Allocation in Commodity Markets
• 2  Passive Investment Strategies in Commodity Markets
• 3  Active Investment Strategies in Commodity Markets
• 4  Financialization of Commodity Markets
• 5  Performance Measurement of Commodity Investments
• 6  Commodity Investments in Financialized Markets—a Study
• Conclusions
• Notes
• Bibliography
• Index