Managed Futures: Is It an Asset Class?

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For those unfamiliar with the term managed futures, it is a niche sector of alternative investments that evolved out of the Commodity Futures Trading Commission Act of 1974, and refers to professionally managed assets in the commodity and financial futures markets. Management is facilitated by either Commodity Trading Advisors (CTAs) or Commodity Pool Operators (CPOs) who are regulated by the Commodity Futures Trading Commission (CFTC) and the National Futures Association (NFA).

Managed futures is the little kid brother to the hedge fund juggernaut. Even so, its impact upon the industry is writ large in two significant and related ways: first, managed futures unlike its brethren hedge funds operate in a highly regulated environment; second, this same regulated environment which imposes disclosure and reporting requirements lends itself to fomenting lower barriers of entry for new talent to evolve. Interestingly, the institutionalization of alternative investments can be traced back to the development of managed futures performance tracking databases first established around 1979. This data became the basis for an academic body of research on managed futures beginning with the seminal study by Harvard Business School professor, Dr. John E. Lintner.

So is managed futures an asset class? Let’s cut to the chase… in this writer’s humble opinion the answer is no, absolutely not. Well, maybe we would reconsider if managed futures was confined to just commodity interests, but with futures contracts also trading on financials, managed futures is as much an asset class as are registered investment advisers, mutual funds or hedge funds.

Lee, Malek, Nash and Rose (2006), on the other hand, would beg to differ. Their paper The Beta of Managed Futures makes the case that the predominant strategy in this space is trend following, and thus an appropriate benchmark for managed futures is one that mechanically mimics trend following systems. To say the least, it’s an interesting approach, and one which addresses issues related to peer group analysis and indices based on a composite of individual CTA programs. As Lee, Malek, Nash and Rose posit, “CTA indices represent the result of investing in CTAs, not the results of investing like CTAs.”

The weak part of their thesis, however, has to do with the assumption that managed futures essentially represents just trend following strategies. Lee, Malek, Nash and Rose readily admit that CTAs “employ a wide range of methods” and that such methods are “by no means exhaustive,” and include “breakout systems, systems based on moving averages and systems based on pattern recognition”. They attempt to reconcile this issue by creating a “beta benchmark” that “consists of twenty systems trading the world’s most liquid… markets”. According to their study, they found that their benchmark, for the period analyzed, was highly correlated to large CTAs.

That said, a mechanical trading index approach still leaves questions, including the validity of the trading methods utilized and the robustness of the parameters used to supposedly define the “beta of managed futures”. At a more subtle level, questions are raised by a relatively new concept proposed by Lo (2004) called the Adaptive Markets Hypothesis (AMH). AMH is based on an evolutionary approach to economic interactions and builds on the research of Wilson (1975), Lo (1999) and Farmer (2002) in applying the principles of competition, reproduction and natural selection.

In light of AMH, the paper by Lawrence Harris, The Winners and Losers of the Zero-Sum Game: The Origins of Trading Profits, Price Efficiency and Market Liquidity provides an intellectually honest answer as to the true dynamics underlying managed futures.

The following is from the paper’s abstract; written in 1993, it is not something you’d likely see in an academic paper nowadays: “Trading is a zero-sum game when measured relative to underlying fundamental values. No trader can profit without another trader losing. People trade because they obtain external benefits from trading… Three groups of stylized characteristic traders are examined. Winning traders trade for profit. Utilitarian traders trade because their external benefits of trading are greater than their losses. Futile traders expect to profit but for a variety of reasons their expectation are not realized.”

Harris goes on to discuss the obvious but little acknowledged fact that, “Trading performance reflects a combination of skill and luck. Successful traders may be skilled traders or simply lucky unskilled traders. Likewise, unsuccessful traders may be unskilled traders or unlucky skilled traders... We would like to believe that skill accounts for most variation in past performance among traders and managers,” but “from past performance alone, you cannot confidently determine who is skilled and who is lucky.” Therein lies the conundrum and the alternative investment industry's dirty little secret.

From this 20,000 foot level, the paper drills down and “examines the economics that determine who wins and who loses when trading.” Harris considers “the styles of value-motivated traders, inside informed traders, headline traders, event study traders, dealers, market-makers, specialists, scalpers, day traders, upstairs position traders, block facilitators, market data monitors, electronic proprietary traders, quote-matchers, front-runners, technical traders, chartists, momentum traders, contrarians, pure arbitrageurs, statistical arbitrageurs, pairs traders, risk arbitrageurs, bluffers, ‘pure’ traders, noise traders, hedgers, uninformed investors, indexers, pseudo-informed traders, fledglings and gamblers.” The paper goes on to “describe each of these traders, explain how their trading generates profits or losses, and consider how they affect price efficiency and liquidity.”

Because this paper was written in the early 1990s some of the descriptions may admittedly be dated relative to technological and quantitative developments in the field of trading since. Nevertheless, Winner and Losers of the Zero-Sum Game is a little noticed gem of a working paper whose astute observations ring true even today despite the escalating arms race in academic working papers being spun out of the university-industry revolving door.

Then why is managed futures constantly referred to as an asset class? Answer: out of laziness. However, such laziness goes beyond just the financial industry’s responsibility; truth is, half the problem lies with investors themselves—try as one might to delineate sophisticated investment concepts, the most common reaction is investors’ eyes glazing over.

So if managed futures is not an asset class, then what is it? As with many of the acronyms and lingo that the financial industry regularly comes up with, mainly for marketing reasons, the term has become a misnomer. What started out as an investment activity that was defined by regulations is now conventionally considered by many an asset class. C'est la vie…

Winners and Losers of the Zero-Sum Game - Harris

References:
Harris, Lawrence. “The Winners and Losers of the Zero-Sum Game: The Origins of Trading Profits, Price Efficiency and Market Liquidity” School of Business Administration, University of Southern California, Draft 0.911, May 7, 1993.

Lee, Timothy C.; Malek, Marc H.; Nash, Jeffrey T.; and Rose, Jeffrey M. “The Beta of Managed Futures,” Conquest Capital Group LLC, February 2006.

Lintner, John E. “The Potential Role of Managed Commodity—Financial Futures Accounts (and/or Funds) in Portfolios of Stocks and Bonds” Presented at the Annual Conference of the Financial Analysts Federation, May 1983.

Lo, Andrew W. “The Adaptive Markets Hypothesis; Market efficiency from an evolutionary perspective” The Journal of Portfolio Management, 30th Anniversary Issue 2004, pp. 15-29.

Using a Zero-Beta Asset for Measuring Variance

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Numerous research papers on gold begin by establishing that of all the commodities gold is a distinct asset. Anecdotal themes include the idea that human civilization has long been enamored with gold going back to ancient times, as well as the fact that, unlike most other commodities, bullion can be stored almost indefinitely and requires very little maintenance. These attributes are given as the reason gold has throughout history been used as a medium of exchange and maintains its purchasing power. In Research Study No. 22, Gold as a Store of Value, published by the World Gold Council in 1998, author Stephen Harmston relates the oft-heard story that "an ounce of gold bought 350 loaves of bread in the time of Nebuchadnezzar… still buys approximately 350 loaves of bread today." Notwithstanding that we have been unable to identify an archeological or biblical source for this tale,[1] let us assume that this bit of trivia is true, along with other stories involving an ounce of gold buying a nice suit, armor or otherwise.

Assuming gold does have the unique ability to maintain consistent purchasing power over an extended period of time, such asset would seem to fit the definition of a zero-beta asset. This is the conclusion of a paper by McCown and Zimmerman (2006) titled, Is Gold a Zero-Beta Asset? Analysis of the Investment Potential of Precious Metals in which they analyze gold returns using three different frameworks: the Sharp (1964) and Lintner (1965) capital asset pricing model (CAPM); the arbitrage pricing theory (APT) of Ross (1976); and cointegration using a test methodology developed by Elliott, Rothenberg and Stock (1996), and another methodology by Kwiatkowski, Phillips, Schmidt and Shin (1992).

Running a regression analysis from 1970 to 2003 where the "risk-free" rate is the yield on the US T-Bill, McCown and Zimmerman use three different proxies for the market portfolio: MSCI US Index, MSCI World denominated in local currency, and MSCI World denominated in US dollar. Acknowledging that the CAPM is "limited in usefulness as a tool for investment analysis," the authors observe that "all of the estimated beta coefficients for gold are statistically indifferent from zero," and therefore gold does not reflect "much, if any, systematic risk". In their CAPM study the conclusion is that gold effectively behaves as a zero-beta asset, yet it also "has a positive risk premium". The APT methodology and cointegration tests also validate the authors' hypothesis.

The paper concludes that gold shows "the characteristics of zero-beta asset," and that the "mean return is just slightly higher than that of T-Bills". Further, "estimates of CAPM and the APT show that both gold and silver bear virtually no market risk, and their estimated betas are statistically indifferent from zero". All three frameworks showed evidence of inflation-hedging ability when added to an investor’s portfolio. Obviously, McCown and Zimmerman's research doesn’t take into account the rise of gold since 2003, which brings up that "old saw" about how correlation does not imply causation. Given that gold is priced today much higher than in 2003, yet inflation has generally been tame since the millennium, raises a question concerning the underlying perspective of this study. Perhaps a better framework for studying gold is that is acts like a currency proxy?

Over the course of our lifetime we are trained to value assets from a US dollar-centric perspective, and it is hard for US-based investors to think differently. In Europe one views prices from a euro-centric perspective. However, it is also possible to revalue the economy and markets from the perspective of preserving purchasing power. When assets such as stocks are revalued in gold as a unit of account, we gain a completely different outlook on whether or not such assets have risen or fallen, and to what extent. For example, if we were to value the Dow Jones Industrial Average, not in US dollars but in ounces of gold, it would have cost around 30 ounces of gold to buy the Average at 10,000 when the index first crossed over that line in 1998. When it crossed over that line again back in October 2009, it would have cost less than 10 ounces of gold.

In a March 30, 2010 Financial Times article titled, "Will negative swap spreads be our coal mine canaries?" Gillian Tett forces us to rethink what constitutes a "risk-free" rate. In finance classes the rate based on the three-month US T-Bill is almost always assumed as the risk-free proxy for input into the CAPM. But what if, as Tett suggests in her article, that there is no risk-free rate? Black's (1972) zero-beta CAPM provides a solution by supposing a riskless asset does not exist, and that investors hold different risky portfolios all existing on the efficent frontier. In order to calculate the zero-beta CAPM, one simply replaces the "risk-free" rate with a "zero-beta" rate. This is necessary to calculate the mean-variance of the market portfolio.[2]

One of the more interesting aspects of McCown and Zimmerman's research was that gold still reflected characteristics of a "zero-beta" asset when using the 'MSCI World denominated in local currency' as a proxy for the market portfolio. When employing the CAPM, analysts traditionally measure portfolio variance denominated in either the US dollar or in the local currency in which the portfolio's assets are actually denominated. What we are suggesting is that zero-beta also implies the idea of relative valuation when measuring variance based on some unit of account. In other words, a better method for measuring variance when using the zero-beta CAPM necessitates an exchange rate constant which consistently maintains purchasing power over an extremely long time horizon, rather than a floating exchange rate variable which reflexively alters the value of the assets it is suppose to measure.

Footnotes:
[1] Dr. Claude Mariottini, Professor of Old Testament, Northern Baptist Seminary, states that no where in the Old Testament does it say that "in the days of Nebuchadnezzar an ounce of gold bought 350 loaves of bread." Further, Dr. Mariottini logically points out that "one must assume that the ounce, a unit of weight in the avoirdupois system, once used in the United Kingdom and still used in the United States, was also used in Babylon. Since the Babylonians did not use imperial units, this statement is false." Source: Gold and Bread http://tinyurl.com/yjxpn6d

[2] Zhang, Lu. "The Capital Asset Pricing Model" Stephen M. Ross School of Business, University of Michigan (2007).

Is Gold a Zero-Beta Asset? Investment Potential of Precious Metals

References:
Harmston, Stephen. "Gold as a Store of Value" Research Study No. 22, World Gold Council (November 1998).

Mariottini, Claude. "Gold and Bread" http://doctor.claudemariottini.com/ (June 10, 2008).

McCown, James Ross and Zimmerman, John R. "Is Gold a Zero-Beta Asset? Analysis of the Investment Potential of Precious Metals" Meinders School of business, Oklahoma City University (July 24, 2006).

Tett, Gillian. "Will negative swap spreads be our coal mine canaries?" Financial Times (March 30 2010).

Zhang, Lu. "The Capital Asset Pricing Model" Stephen M. Ross School of Business, University of Michigan (2007).

Alpha-Beta and the Heisenberg Uncertainty Principle

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In physics, complementarity is a basic principle of quantum theory closely identified with the Copenhagen interpretation, and refers to effects such as "wave–particle duality," in which different measurements made on a system reveal it to have either particle-like or wave-like properties. Niels Bohr is usually associated with this concept, which he developed at Copenhagen with Heisenberg as a philosophical adjunct to the mathematics of quantum mechanics and in particular the Heisenberg uncertainty principle. The Heisenberg uncertainty principle states that certain pairs of physical properties, like position and momentum, cannot both be known with precision. That is, the more precisely one property is known, the less precisely the other property can be known.

In Chinese philosophy, the concept of "yīn yang" is used to describe how polar or seemingly contrary forces are interconnected and interdependent in the natural world, and how they give rise to each other in turn. Yin yang are complementary opposites within a greater whole. Everything has both yin and yang aspects, although yin or yang elements may manifest more strongly in different objects or at different times. Yin yang constantly interacts, never existing in absolute stasis as symbolized by the Taijitu symbol.

A similar paradox exists within the CAPM paradigm involving the relationship between the concept of "beta," as determined by the market portfolio, and "alpha," which loosely represents "a proxy for manager skill". As is inferred by our prior posting, "The CAPM Debate and the Search for 'True Beta'", the yin yang "whole" relates to the "True Beta" concept which Jagannathan and Wang (1996) theorized must encompass "the aggregate wealth portfolio of all agents in the economy". Moreover, one could apply aspects of "beta" to the symbology associated with "yin," which is usually characterized as slow, diffuse, tranquil, femininity and night; and apply aspects of "alpha" to the symbolism of "yang," which by contrast is characterized as fast, hard, focused, masculinity and day.

Schneeweis (1999) investigates this alpha-beta paradox in his article, "Alpha, Alpha, Whose got the Alpha?" wherein he writes about the problem of measuring "alpha" by raising the question of "how to define the expected risk of the manager’s investment position". In other words, when marketing "alpha" portfolio managers often assume "the reference benchmark is the appropriate benchmark and that the strategy has the same leverage as the benchmark". Unfortunately, "[w]ith the exception of a strategy that is designed to replicate the returns of the benchmark, the alpha generated by this approach is essentially meaningless". Hence, investors often mistakenly rely on a single-index model as a meaningful benchmark from which to gauge the factors "driving the return of the strategy," when often a "multi-factor model should be used to describe the various market factors that drive the return strategy". The problem is that statistically it is "better to over-specify a model… than to under-specify. If the model is over-specified, many of the betas will simply be zero. However, if under-specified, there is the possibility of significant bias".

Which brings us back to the Heisenberg uncertainty principle...

Just like the physical properties of position and momentum cannot both be known with precision, the properties of "alpha" and "beta" also cannot be measured precisely. This statement can be interpreted in two different ways: According to Heisenberg its meaning is that it is impossible to determine simultaneously both properties with any great degree of accuracy or certainty. However, according to Ballentine and others this is not a statement about the limitations of a researcher's ability to measure particular quantities of a system, but it is a statement about the nature of the system itself as described by the equations.


Alpha Alpha Whose Got the Alpha - Schneeweis

References:
Ballentine, L.E. The statistical interpretation of quantum mechanics, Rev. Mod. Phys. 42, 358–381 (1970).

Bohr, Niels. "Atomic Physics and Human Knowledge," p. 38.

Heisenberg, W. "Über den anschaulichen Inhalt der quantentheoretischen Kinematik und Mechanik," In: Zeitschrift für Physik. 43 1927, S. 172–198.

Jagannathan, Ravi; McGrattan, Ellen R. (1995). "The CAPM Debate" Federal Reserve Bank of Minneapolis Quarterly Review, Vol. 19, No. 4, Fall 1995, pp. 2-17.

Jagannathan, Ravi; Wang, Zhenyu (1993). "The CAPM is Alive and Well" Research Department Staff Report 165. Federal Reserve Bank of Minneapolis.

Jagannathan, Ravi; Wang, Zhenyu (1996). "The Conditional CAPM and the Cross-Section of Expected Returns" Journal of Finance, Vol. 51, No. 1, March, pp. 3-53.

Schneeweis, Thomas (1999). "Alpha, Alpha, Whose got the Alpha?" University of Massachusetts, School of Management (October 5, 1999).

The CAPM Debate and the Search for "True Beta"

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Conventional investment theory states that when an investor constructs a well-diversified portfolio, the unsystematic sources of risk are diversified away leaving the systematic or non-diversifiable source of risk as the relevant risks. The capital asset pricing model (CAPM), developed by Sharpe (1964), Lintner (1965) and Black (1972) [zero-beta version], asserts that the correct measure of this riskiness is its measure known as the "beta coefficient" or just "beta". Effectively, beta is a measure of an asset’s correlated volatility relative to the volatility of the overall market. Consequently, given the beta of an asset and the risk-free rate, the CAPM should be able to predict the expected return for that asset, and correspondingly the expected risk premium as well.

This explanation is textbook. However, unbeknownst to most investors, there has been a long running argument in academic circles on the CAPM and other pricing models, even within the milieu of traditional investments. Without going into the details of this debate, certain empirical studies have revealed "cross-sectional variations" in the CAPM questioning the validity of the model. In direct response to the challenge by Fama and French (1992), Jagannathan and Wang (1996) theorized that “…the lack of empirical support for the CAPM may be due to the inappropriateness of some assumptions made to facilitate the empirical analysis of the model. Such an analysis must include a measure of the return on the aggregate wealth portfolio of all agents in the economy.”

Financial institutions have not been left behind by these evolving academic theories. Index creation and benchmarking has become standard fare, and since the introduction of 'exchange traded funds' (ETFs), a veritable industry has developed around the "multiple beta" concept. But by no means has the plethora of these instruments captured every aspect of the aggregate wealth portfolio of all agents in the global economy, although at the current pace of ETF development it would seem that this is the undeclared objective.

Such backdrop is the principal context which gives impetus to the notion of "exotic betas". The term, a recent addition to the investment lexicon which evolved from ideas advanced by proponents of alternative investments, suggests that certain alternative investment assets and/or strategies, representing commonly pursued market paradigms, can be identified, tracked and replicated employing a predefined passive approach/model similar to traditional index construction.

This leaves open the question as to whether institutions, through sophisticated financial engineering, can truly capture in a passive way all possible sources of return in the global economy. Or, does some aspect which the industry loosely calls alpha (i.e., skill-based returns) always remain outside the grasp of such institutions’ arbitrary models of beta?

Jagannathan - The CAPM Debate

References:
Black, Fischer (1972). “Capital Market Equilibrium with Restricted Borrowing” Journal of Business 45, July, pp. 444-455.

Fama, Eugene F.; French, Kenneth R. (1992). “The Cross-Section of Expected Stock Returns” Journal of Finance 47, June, pp. 427-465.

Jagannathan, Ravi; McGrattan, Ellen R. (1995). “The CAPM Debate” Federal Reserve Bank of Minneapolis Quarterly Review, Vol. 19, No. 4, Fall 1995, pp. 2-17

Jagannathan, Ravi; Wang, Zhenyu (1993). “The CAPM is Alive and Well” Research Department Staff Report 165. Federal Reserve Bank of Minneapolis

Jagannathan, Ravi; Wang, Zhenyu (1996). “The Conditional CAPM and the Cross-Section of Expected Returns” Journal of Finance, Vol. 51, No. 1, March, pp. 3-53.

The Mysterious Case of an Enigma within a Paradox

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In 1995, Cambridge University Press published in its Journal of Economic History an article by John R. Garrett titled, "Monetary Policy and Expectations: Market-Control Techniques and the Bank of England, 1925-1931". Garrett begins by referencing Richard Sayers who, as the official Bank of England historian with full access to confidential archives, revealed in a 1976 book titled, "The Bank of England 1891-1944," that the Bank had influenced interest rates by manipulating reported gold flows between 1925-1931. Based on such enigmatic evidence, Garrett (1995) "models expectations manipulation as a monetary policy channel," and shows that "gold flow falsification was over two-thirds as effective as an open-market operation."

As Garrett noted, "These results contradict accepted new classical models and suggest that credibility benefits from new classical policy are small." The enigma within a paradox relates to the concept of 'rational expectations' as described below:

Our working paper investigated various models which deal with the potential sources of return to speculators in the futures market, including one of our own which exemplifies the complexity of these markets. Admittedly, models are only an abstraction from reality. Expecting such models to be exactly right is unreasonable, and it is generally understood that neoclassical economic theory has inherent limitations related to the analysis of markets within the context of “rational equilibrium systems.” Such systems are based on perfect competition, and assume markets naturally return to equilibrium after a disturbance. Hence, modern finance seeks to maximize utility and/or profits in a world of constraints based on the choices of “rational” economic agents. By definition then, these models relegate speculators to the role of that very agent which maintains equilibrium. Yet a survey of real-life speculators reveals that these practitioners do not as a general rule use academic models in their day-to-day trading decisions. Paradoxically, this same group plays a key influence upon the selfsame futures data from which such models are constructed. So if the data series is assumed to represent equilibrium and “the future is merely the statistical reflection of the past,” then one could inversely argue that perfect competition and rational expectations minimize these models’ usefulness as a mechanism from which to make speculative decisions. In other words, rational expectations compel such models to simply validate that current price data is equal to equilibrium, unless the opposite is true—that markets are in fact imperfect and rational expectations is untenable, which in turn undermines the veracity of these models. [Source: The Search for the Beta of Commodity Futures]

Following the twists and turns in this "riddle, wrapped in a mystery, inside an enigma" is the implication that the 'rational expectations equilibrium' paradox is being turned back on itself by the central banks themselves. It is not just that central banks are using game theory to manage expectations (and by implication models based on rational expectations), the 1925-1931 Bank of England episode illustrates a situation where economic reality was changed by a central bank despite it being based on a lie. In Garret's words:

Markets can not tell when a central bank is lying. They then have the option to accept all or reject all forecast information emanating from the central bank. Under such circumstances the credibility model asserts that private financial markets reject all central bank information. This is possible because the financial markets' private information is assumed to be almost com- plete. However, the results presented here contradict this assumption and lend support to the opposite case: the markets' private information is so incomplete that they can not dispense with central-bank sources. The implication for the credibility model is devastating because perva- sive ignorance and uncertainty allow the central bank to maintain its position as a disseminator of forecast information even if the central bank is guilty of extreme dishonesty, as under Norman. Under these circumstances monetary policy will be an effective instrument to stabilize the economy against both money demand and real shocks, which contradicts the core result found in the large and influential credibility-model literature.

The article "Priceless: How The Federal Reserve Bought The Economics Profession" adds support to this idea of an enigma within a paradox, and lends credibility to concerns of economic/market groupthink. In the words of Morpheus: "I imagine that right now, you're feeling a bit like Alice. Hmm? Tumbling down the rabbit hole?"

John Garrett - Monetary Policy and Expectations

References:
Garrett, John R. (1995) "Monetary Policy and Expectations: Market-Control Techniques and the Bank of England, 1925-1931" The Journal of Economic History, Cambridge University Press, Sept. 1995, pp. 612-636

Frankfurter, Mack and Accomazzo, Davide (2007) "Is Managed Futures an Asset Class? The Search for the Beta of Commodity Futures" (December 31, 2007). Available at SSRN: http://ssrn.com/abstract=1029243