Overview: A risk parity portfolio framework can be quite helpful when constructing portfolios of multiple differentiated investment opportunities. In this paper, we used this framework to combine managed futures with a portfolio dominated by stocks and bonds. Spreading risk equally among those three investment opportunities and re-balancing frequently- something made possible in practice recently by the emergence of managed futures mutual funds z- could lead to portfolio’s return stream that is smoother and with shallower drawdowns as compared to a traditional 60/40 allocation scheme. When adopting this framework the “math” suggests an allocation to managed futures somewhere in the 15-25% range. The paper also discusses recent performance of managed futures. We believe there are a number of reasons for the disappointing performance within the managed futures industry over the past two years, including volatility that has contracted to below historically normal levels, correlations between markets that have been high, aggressive government and central bank intervention that has likely muted trends, and the commodity and currency asset classes that have been a consistent drag on performance. The question to ask is: Are all of these phenomena likely to continue over the coming years? If the answer is yes then trend followers will be challenged. We, however, think it is more likely that some of the phenomena negatively affecting managed futures performance will soon return to more normalized levels and the period of 2011- 2012 will eventually be remembered as a period of frustration for the strategy that still presents a valid and differentiated investment opportunity
Overview: Investors and money managers interested in diversifying into Managed Futures are often attracted to the daily transparency and better liquidity that Managed Futures have over the typical hedge-fund structure. Professional money managers in the Managed Futures space are known by the regulatory designation of Commodity Trading Advisors (CTAs). However, with hundreds of CTA programs from which to choose, it can be daunting to know where to start one’s analysis of this investment space. One place to begin is with CTA indexes, which compile and track the performance of different CTA programs. This paper summarizes and analyzes information on over ten CTA indexes, and while it attempts to encompass the most-oft used indexes, it is not a completely exhaustive list. Finally, since much of this information is not readily available, the purpose of this paper is to serve as an effective and efficient informational resource for the industry going forward. Upon delving into this material one quickly discovers there are differences between the various CTA indexes in terms of construction methodology, the number of CTA programs tracked, and minimum requirements with regard to track record length, financial auditing, and assets being managed.
Overview: CTA returns have been lackluster in recent years. This has led some observers and investors to question the value and benefits of Managed Futures within a portfolio. The CTA VAITM (Valued Added Index) was developed to demonstrate that Managed Futures strategies consistently add value over the long term (not only in times of financial crisis). Additionally, this paper demonstrates how the CTA VAITM can be used to implement a simple market timing strategy that can further improve portfolio performance.
Overview: This paper explores a number of features considered to be important when assessing Commodity Trading Advisors (CTAs) from the perspective of an investor in the asset class as well as issues of a more technical nature which we hope will inform further those considering making an allocation to the sector. Throughout the paper, topics are visited which are pertinent to this quest and, in so doing, we limit re-visiting themes which are already much discussed; instead we illustrate our assertions (where possible and appropriate) with technical data and examples of the techniques developed for finding, managing and monitoring managers in the space.
Overview: This paper examines five very popular myths and misconceptions held by both retail and institutional investors regarding managed futures. These myths have persisted for several years. As investors are becoming more aware of the potential use of managed futures for asset allocation and portfolio diversification, knowing if the myths are true or false, is critical for an investor’s understanding and appreciation of managed futures.
Overview: Much has been written about the low correlation between managed futures strategies and the S&P 500. However, over certain periods the correlation between the two can be quite high. In our research note Superstars versus Teamwork, we showed the distribution of estimated pairwise correlations is broad and symmetrical when the true correlation is low (i.e. large sampling error). Given a correlation of -0.16 between the Newedge CTA Index and S&P 500 since January 2000, one should expect to see periods of relatively high positive correlation. Even so, intervals of increased correlation still have real implications for a portfolio of diversified trading strategies. In this snapshot, we analyze returns of the S&P 500 and the Newedge CTA Index conditional on periods of relatively high correlation and find CTA returns appear to be independent of S&P 500 performance irrespective of
correlation levels. Second, when correlations between the two indices are high, the S&P 500 exhibits significant positive performance.
Overview: Most investment strategies are susceptible to suffering devastating losses during equity market crisis. Given this, for almost any investor, the key to finding true diversification is in finding an investment which is able to deliver performance during these turbulent periods. The recent losses of the credit crisis have also reinforced to investors the importance of understanding why a particular investment strategy makes sense. For any new or current investor in managed futures, it is well known that these strategies tend to perform well when equity markets take losses making them an excellent candidate for diversifying a portfolio. By taking a closer look into what really happens during equity market crisis events (often called tail risk events), this investment primer will take a new approach to explaining managed futures and explain why they can deliver “crisis alpha” opportunities for their investors. Crisis alpha opportunities are profits which are gained by exploiting the persistent trends that occur across markets during times of crisis. By gaining an understanding of why managed futures can deliver crisis alpha, the commonly cited benefits and characteristics which describe the strategy can be explained in simpler terms helping investors to more effectively use the investment strategy as part of a larger investment portfolio
Overview: Managed futures comprise a wide array of liquid, transparent alpha strategies which offer institutional investors a number of benefits. These include cash efficiency, intuitive risk management, and a proclivity toward strong performance in market environments that tend to be difficult for other investments. This paper revisits John Lintner’s classic 1983 paper, “The Potential Role of Managed Commodity-Financial Futures Accounts (and/or Funds) in Portfolios of Stocks and Bonds,” which explored the substantial diversification benefits that accrue when managed futures are added to institutional portfolios. As Lintner did, this paper analyzes the portfolio benefits that managed futures offer through the mean-variance framework, but it draws on more complete techniques such as the analysis of omega functions to assess portfolio contribution. The paper also conducts a comparative qualitative and quantitative analysis of the risk-and-return opportunities of managed futures relative to other investments, and includes a discussion as to why managed futures strategies tend to perform well in conditions that are not conducive to other investment strategies. It provides an overview of the diversity of investment styles within managed futures, dispelling the commonly held notion that all CTAs employ trend-following strategies. Finally, it highlights the opportunities the space offers to pension plan sponsors, endowments and foundations seeking to create well-diversified, liquid, transparent, alpha generating portfolios.
Overview: In this paper, we rigorously establish a relationship between time-series momentum strategies in futures markets and commodity trading advisors (CTAs) and examine the question of capacity constraints in trend-following investing. First, we construct a very comprehensive set of time-series momentum benchmark portfolios. Second, we provide evidence that CTAs follow time-series momentum strategies, by showing that such benchmark strategies have high explanatory power in the time-series of CTA index returns. Third, we do not find evidence of statistically significant capacity constraints based on two different methodologies and several robustness tests. Our results have important implications for hedge fund studies and investors.
Overview: From its original position atop the retail and high net worth investor’s “risk pyramid’; the Liquid CTA/Macro industry has broadened out to become a core portfolio component for institutional investors of all flavors in recent years- from public and corporate pensions to endowments and foundations to family offices. Positive, uncorrelated performance during the 2008 Global Financial Crisis helped accelerate this expansion in the industry’s investor base. Yet, the industry itself also changed to accommodate this new institutional base. To absorb the extensive asset flows originating from institutions, the industry sought means to extend its capacity and reduce portfolio volatility. We are now seeing managers list their funds on institutionally-focused capital raising platforms and developing their own hedge fund-like marketing teams to directly raise assets. All of these factors are working to move Liquid CTA/Macro managers into the mainstream.
Overview: This brief white paper provides a quick introduction to the Managed Futures industry. It addresses the key characteristics which benefit investors highlighting the potential advantages of including Managed Futures in a diversified portfolio. Characteristics described in the paper include the diversification benefits, non-correlation to equities and traditional asset classes, transparency, liquidity, non-directionality, and cash-efficiency. The paper also provides a general overview of the strategies represented within the Managed Futures asset class.
Overview: This paper illustrates the portfolio construction technique of blending managed futures with other types of hedge fund strategies.It furnishes evidence that the benefit of including managed futures with other types of hedge fund strategies makes for a superior risk adjusted return when compared to non-CTAs alone. Moreover, the sweeping technique is illustrated to help demonstrate how different calibrations from a risk- budgeting perspective correspond to different target objectives. The techniques in this paper could potentially be of particular importance to pensions and endowments that are facing challenges from an asset-liability perspective.
Overview: In November 2002, Cass Business School Professor Harry M.Kat, Ph.D.began to circulate a Working Paper entitled Managed Futures and Hedge Funds: A Match Made in Heaven. The Journal of Investment Management subsequently published the paper in the First Quarter of 2004. In this paper, we revisit and update Kat’s original work. Using similar data for the period June 2001- December 2011, we find that his observations continue to hold true more than 10 years later. During the subsequent 10 years, a highly volatile period that included separate stock market drawdowns of 36% and 56%, managed futures have continued to provide more effective and more valuable diversification for portfolios of stocks and bonds than have hedge funds.
Overview: This study investigates the differences in mortality between systematic and discretionary Commodity Trading Advisors, CTAs, over 1994-2009 period, the longest horizon than any encompassed in the literature. This study shows that liquidation is not the same as failure in the CTA industry. New filters are proposed that allow identifying real failures among funds in the graveyard database. By re-examining the attrition rate, this study finds that the real failure rate is in fact 11.1% in the CTA industry lower than the average yearly attrition rate of 17.3%. Secondly this study proposes a new way to classify CTAs, mainly into systematic and discretionary funds and provides detailed analysis of their survival. Systematic CTAs are found to have higher median survival than discretionary, 12 years vs.8 years. The effect of various covariates including several downside risk measures is investigated in predicting CTA failure. Controlling for performance, HWM, minimum investment, fund age, leverage and lockup, funds with higher downside risk measures have a higher hazard rate. Compared to the other downside risk measures, volatility of returns is less able to predict failure. Fund flows have significant and positive effect on the probability of survival, funds that receive larger inflows are able to survive longer than funds that do not. Finally larger systematic CTAs have the highest probability of survival.
Overview: Hedge funds have experienced significant growth over the last few decades. Assets under management have grown from an estimated $100 billion in 1995 to more than $1.7 trillion as of 4th Quarter 2012. As a rapidly maturing investment alternative, hedge funds can offer investors increased opportunities to receive positive returns, enhance diversification, lower volatility and improve overall risk-adjusted returns. This paper discusses one particular hedge fund style known as “systematic global macro; first reviewing this style’s risk and performance characteristics, and then discussing why it should continue to be a successful and essential component of a diversified portfolio that invests across a variety of hedge fund strategies.
Overview: Key points of the paper are: High market volatility has driven the development of investment strategies advertised to deliver reduced risk without reduced return; The “low-volatility” equity anomaly (low-risk stocks may have similar or greater returns than high-risk stocks) is best exploited by investors as part of the toolkit of a broader active strategy; “Tail risk” strategies can provide protection in extreme market events, but their persistent negative; carry (ongoing cost) make them unappealing to most investors; Managed futures and global macro hedge fund strategies have desirable downside risk protection characteristics combined with positive returns and alpha for skilled investors; Clients can increase their downside protection by allocating part of their hedge fund or opportunistic asset category to managed futures and global macro strategies.
Overview: Taken together, the different methods we have examined point to several useful properties of CTA strategy performance resulting from its systematic, data-driven investment approach. 1. Through stepwise regression in short windows, the variability of the CTA strategy’s beta can be observed. The strategy often demonstrates favorable, directional beta exposure during rising and falling broad markets. 2. Fung and Hsieh’s straddle model captures the convexity of the strategy; the straddle transformation illustrates the strategy’s “long volatility” return properties, regardless of whether underlying managers are literally holding straddles. 3. The moving average method utilizes a trend-following technique to better capture the time-varying nature of CTA exposures…..CTA returns have demonstrated substantial long-term diversification properties in the context of a broad, multi-asset class policy portfolio. They also represent one of the few investment strategies that have the potential for outsized positive returns during extended periods of market stress.
Overview: Investors who have diversified their portfolios may sometimes find themselves gazing longingly at the returns they could have enjoyed if they had only stayed in stocks. Most of us know the responsible choice is to diversify and protect your portfolio frompotentially catastrophic losses. But that expectation of future benefits doesn’t make it any easier to ignore the feeling of missing out. And unfortunately for those who diversified since the financial crisis in 2008, the last few years have been tough to watch as stocks have soared to leave the diversifiers in the dust. But evaluating the diversified portfolio when stocks are climbing is akin the weighing the value of flood insurance in the midst of a drought. Things may look fine now, but how much longer would this rally need to last before gains in stocks outweigh the benefits of diversification during another crash? We take a look at the numbers.
Overview: We study the performance of trend-following investing across global markets since 1903, extending the existing evidence by more than 80 years. We find that trend-following has delivered strong positive returns and realized a low correlation to traditional asset classes each decade for more than a century. We analyze trend-following returns through various economic environments and highlight the diversification benefits the strategy has historically provided in equity bear markets. Finally, we evaluate the recent environment for the strategy in the context of these long-term results.
Overview: Trend-following is the most common strategy employed in the managed futures world, and plays a key role in the asset class’ unique performance profile of gains during stock market downturns. But over the last few years, poor performance has plagued trend-following commodity trading advisors. Many of the trend followers we track are experiencing drawdowns of 15 to 20 months or more, and a select few have failed to make new equity highs following the boom times of 2008. Further struggles are evident in the dismal performance of trend-following sub-indices. It’s allied to more than a couple people we’ve talked to recently uttering those words the contrarian in us loves to hear:” is trend-following dead”? But this obituary has been written before, and the nature of trend-following is to offer middling returns while waiting for opportunity to strike. So is this time different? We have reason to think that far from being laid to rest, trend-following is in fact poised for a breakout.
Overview: How can the behavior of markets be viewed in the context of kurtosis? When kurtosis is the subject, most people acknowledge the major importance of fat tails, but not everyone really comprehends the underlying processes. The biggest mistake with respect to a high kurtosis is to concentrate completely on the fat tails and ignore the ‘high peak’. These fat tails would not be there without the high peak. In fact, a high kurtosis is more often caused by processes that directly contribute to a high peak than by processes that directly contribute to fat tails. The article discusses this and the dangers in a hidden exchange of standard deviation for kurtosis. Higher risk can hide in the higher kurtosis despite what may be a lower standard deviation. Investors should be alert to the possibility of having a false sense of security.
Overview: Investors allocate to long-term trend followers in part because they performed admirably in 2008 (and steadily prior to 2008). Since then, however, performance has been mixed. Is this under-performance due to a tough environment or alpha decay? When will trend following make money again? The common perception is that trend followers are ‘long volatility’: they make money when asset markets are down significantly or up significantly, and lose money when markets go nowhere. Recent performance, however, belies this notion. The strategy delivered uneven returns during periods of punctuated crisis (May 2010 flash crash) and during periods of extended down (summer of 2011) and up markets (Q3 & Q4 of 2012). This paper gives investors a new framework to conceptualize when trend following works. We show that trend followers are neither long nor short volatility, and neither long nor short correlation. Instead, one must consider correlation and volatility jointly to explain their performance.
Overview: We think backfill bias is a natural result of the research process and arises when a manager is constructing an entirely new program or adding a new model to an existing program. In its simplest form, a manager begins by developing an investment thesis, then constructs the strategy using in sample data and tests on an out of sample data set. If the strategy performs as expected the manager will allocate a small amount of capital and commence live trading. It is at this point that backfill is created. The manager is still “testing” the strategy and will hope to attract outside capital if successful. Otherwise, if performance is negative or outside of reasonable expectations, the manager may discontinue trading and revert to additional development and testing. This behavior is completely aligned with what we should expect from all actively managed investment opportunities. So if backfill data are biased are they still useful? Perhaps, but we feel care should be taken and that it is constructive to know which part of the manager’s track record is backfill when analyzing historical data. As the circumstances will obviously differ from manager to manager, having a framework for dealing with this type of bias may help set the appropriate performance expectations going forward.
Overview: As is the case in every asset class under the sun, managed futures investors love to chase performance. The sustainability of a strategy often comes second to double or even triple digit returns. We do our best to discourage such decision making, because in our experience, this is uniquely damaging in managed futures allocations.The fact is that drawdowns- or extended periods of severe losses- are a fact of life for managed futures investors. There is no way to avoid them; every program goes through them. But in our experience, performance tends to be cyclical for quality programs. They will have a run up, face a drawdown, experience a recovery period, and repeat the process all over again. An investor making allocations at the peak of a run up period usually sets themselves up for losses in the short-term – losses that typically don’t sit well with an investor who was chasing returns in the first place.
Overview: In this research note we: describe the data sets that we used to establish the presence and persistence of autocorrelation in CTAs’ returns; present a drawdown puzzle involving the 67 CTAs who had ever appeared in the Newedge CTA Index that brought the importance of autocorrelated returns to our attention; show how autocorrelated returns provide the key to unlocking the puzzle and the effect autocorrelation has on the way we should translate single-period volatilities into multi-period volatilities; report on what we found when we examined other data sets of CTA returns; return to the global equity/CTA comparison; and conclude the note with an analysis of how autocorrelation affects risk and biases our measures of risk-adjusted returns in a potentially big way.
Overview: Many traders and investment managers have the desire to measure and compare CTA managers and/or trading systems. We believe risk-adjusted returns are one of the most important measures to consider since, given the inherent free leverage of the futures markets, more return can always be earned by taking more risk. The most popular measure of risk-adjusted performance is the Sharpe ratio. While the Sharpe ratio is definitely the most widely used, it is not without its issues and limitations. We believe the Sortino ratio improves on the Sharpe ratio in a few areas. The purpose of this article, however, is not necessarily to extol the virtues of the Sortino ratio, but rather to review its definition and present how to properly calculate it since we have often seen its calculation done incorrectly.
Overview: This paper reviews the performance metrics and use of alternative asset allocations within a traditional asset portfolio. We show most asset classes are not Gaussian (bell-shaped) normal curves as modern portfolio theory assumes returns to be. Instead, the returns are asymmetrical to the right or left causing the employment of higher statistical moments such as skewness and kurtosis to determine risk-adjusted returns. Therefore, the first and second statistical moments (mean and variance) are not sufficient to determine risk-adjusted returns of a portfolio. Utilizing higher moments in conjunction with volatility parsed between upside and downside returns, we demonstrate how managed futures and hedge funds perform individually and simultaneously as diversifiers in a traditional portfolio.
Overview: The global financial crisis (GFC) of 2007-08 was remarkably severe not only in the magnitude of drawdowns suffered by individual asset classes, but also the drawdowns of portfolios thought to be well diversified. The risk of such an outcome has come to be labeled tail risk in reference to the extreme left tail of an asset’s or portfolio’s return distribution. Since the GFC, many investment organizations have launched tail risk protection strategies designed to address such periods of severe market distress. Likewise, flows into managed futures strategies (commonly thought to profit during periods of elevated volatility) increased dramatically. This paper measures the benefits and costs of several candidate tail risk protection strategies empirically using more than 20 years of monthly data from U.S. markets. We analyze four methods for controlling tail risk: (1) long volatility, (2) low volatility
equity, (3) trend following, and (4) equity exposure management.
Overview: The aim of this paper is to examine the effect of risk-weighting and of the choice of trading signal on the performance of time series momentum strategies using a broad data set of 75 futures contracts over the period 1974·2013.Time-series momentum strategies have received increased attention after they provided again, as in previous business cycle downturns, impressive diversification benefits during the recent financial crisis in 2008. Motivated by recent asset pricing literature that examines the effect of frictions on asset prices and the link between portfolio volatility and turnover, we highlight the effect of the choice of volatility estimator and trading signal on turnover and performance of time-series momentum strategies. We find that by increasing the efficiency of volatility estimation using estimators with desirable theoretical properties, such as range-based estimators, the net of transaction costs performance improves, but the effect on turnover is relatively small compared to that of the trading signal. Momentum trading signals generated by fitting a linear trend on the asset price path maximize the out-of- sample performance by reducing portfolio turnover by about two thirds, hence dominating other momentum trading signals commonly used in the literature.
Overview: This paper illustrates that investors often mistake illiquidity for alpha, and that investors are often not giving proper value to liquidity. The concepts of liquidity buckets, liquidity indices, and liquidity duration are introduced. The application of liquidity buckets demonstrates that illiquid hedge funds did not perform better, in a pure statistical manner, than liquid hedge funds during the time period of June 2004 to June 2007 (note that this time period is prior to the financial crisis). This paper furnishes evidence that investors are often not being properly compensated for illiquidity.
Overview: The year 2011 was a period fraught with turbulence in financial markets. Managed futures strategies, despite their common association with long volatility, did not fare as well as some might have expected amidst this turbulence. A closer look at volatility, what it means to be long or short volatility, and managed futures performance across different regimes in volatility can provide insights into the strategy’s complex or “convex” relationship with volatility. A closer look at the cycles of volatility demonstrates that managed futures is able to capture “crisis alpha” for investors over negative volatility cycles, while in certain turbulent periods they also face some of the same “short volatility” risks that plague many hedge fund strategies.
Overview: This paper explains how the Omega function may be used to help “tame the tail”. One should not penalize for upside volatility, and one should take into consideration the higher statistical moments. The Omega function lends itself particularly well to pensions and endowments, since the Omega threshold allows these groups to view the measurements in perspective with their asset-liability situation. Some qualitative due diligence and risk management insights are also shared.
Overview: The Global Financial Crisis brought with it a resurgence of interest in tail risk, both within the financial services industry and the academic world. However, tail risk has been an important topic in financial literature since academic researchers realized that market returns often violate normality assumptions. In this article, we provide a brief literature review of the evolution of tail risk measures, as well as research on tail dependency. We also document a number of academic studies that assess tail risk and tail dependency of hedge fund returns. The literature related to tail risk and its measurement dates back to the early 1960’s.
Overview: A game-theoretic example is presented that helps to illustrate the value of liquidity. These insights are applicable to hedge fund investors since hedge funds have different lock-up and redemption terms. This game also shows the danger of relying on intuition to determine the value of liquidity. It is also demonstrated that the value of liquidity is different for different types of investors; the value is less for investors with less ability. Liquidity has become an increasingly important issue in the alternative investments and derivatives space, and this paper provides some quantitative insights on the value of liquidity.
Overview: This quantitatively technical paper extends the work from the paper “The Value of Liquidity”. The Balls in the Hat game is examined in the asymptotic case. It helps to further establish that, from a behavioral finance perspective, humans are wired in such a way that we tend to underestimate the value of liquidity. Quantitative techniques, including the Omega Robustness Coefficient, areinvoked to contribute to the understanding of the mathematics of liquidity.
Overview: When investors think of risk, they usually associate it with volatility. This probably stems from Nobel Prize winning economist Harry Markowitz’s use of volatility in the 1950s and fellow Nobel Prize winner William Sharpe’s use of volatility in creating his self-named method of risk adjusting returns. The lower the volatility of a given investment theoretically indicates that investment carries less risk. Risk, however, could be viewed from a different angle. The impact of a high volatility investment on a portfolio can be mitigated by the allocation size given to that product. By normalizing for volatility, theoretically, high and low volatility investments can have equal impact on a portfolio’s total return. This leads us to a different way to view risk. Risk is the difference between the anticipated worst loss and the realized worst loss. When viewed through this lens, lower volatility equals higher risk. Seeking rather than avoiding volatility can lead to a lower cost, more liquid portfolio with a reduced level of risk and an increased potential of returns.
Overview: The growth of the managed futures industry increased dramatically in the late 1970s following the introduction of the world’s first financial futures contracts (foreign currency futures) by the Chicago Mercantile Exchange in 1972. The first academic research on the performance of managed futures was published in the 1980s. Researchers who adopted similar performance metrics to assess managed futures in a different time periods also reached similar conclusions as earlier studies about the benefits of managed futures. Some recent studies also address the issues of performance persistence and market timing ability of managed futures traders. Following the onset of the financial crisis of 2007-2008, researchers also reassessed the diversification benefits of managed futures and the low correlations of their returns with those of stocks and bonds. Evidence reaffirmed that the favorable haracteristics of managed futures investments were useful for investors looking for “crisis alpha” for their portfolios in periods with high market volatility.
Overview: In response to the 2008 financial crisis, investors began to recognize the importance of real diversification. After a strong bull run in equity markets, and a more than 30-year decline in fixed income yields, investors are once again looking at alternatives for their potential to withstand periods of market crisis. More specifically, they are looking for investments with the potential for significant risk-adjusted returns, lower correlation to traditional asset classes, and reduced portfolio volatility. With the advent of liquid alternatives, the opportunity to invest in alternative investments is more accessible than ever before. Not all funds, however, are created equal.
Overview: This paper reviews the performance metrics and use of alternative asset allocations within a traditional asset portfolio. We show most asset classes are not Gaussian (bell-shaped) normal curves as modern portfolio theory assumes returns to be. Instead, the returns are asymmetrical to the right or left causing the employment of higher statistical moments such as skewness and kurtosis to determine risk-adjusted returns. Therefore, the first and second statistical moments (mean and variance) are not sufficient to determine risk-adjusted returns of a portfolio. Utilizing higher moments in conjunction with volatility parsed between upside and downside returns, we demonstrate how managed futures and hedge funds perform individually and simultaneously as diversifiers in a traditional portfolio.