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In this article, we examine how contango and backwardation affects the performance of commodity hedge funds. Evaluation based on commodity trading advisors', CTA. CTA, commodity trading advisers, or managed futures managers' trade in the commodity market. The hedge funds invest in commodity futures, currencies, bonds and shares. The portfolio is leveraged and the risk is quite high. Forward and futures contracts have similarities in terms that they involve two parties to exchange a commodity, a currency or a bond at a specified price in the future. The costs of carry that characterize these contracts are insurance, storage and interest costs. Backwardation is a case where the futures price is below the spot price. It takes place when there is advantage to hold the underlying asset that offset the opportunity cost of the risk-free rate and additional net holding costs. In contrast, contango is a case where the futures price is above the spot price. In a speculation situation, the futures prices do not equal spot prices and speculators are taking advantage from the mispricing. Speculators are short or long according to if the futures market is in backwardation or in a contango situation. In case, that the investor is not getting dividends, semi-annual coupons or monthly yields and the futures price are less than the spot prices, then, we are discussing about a backwardation effect.
Understanding risk is important. Prior to 2008, as the yields on safe assets hit rock bottom, investors began to focus on an alphabet soup of more complex instruments. These complex securities were rated AAA and appeared as safe as U.S. Treasuries, but with much higher yields. The 2008 financial crisis revealed, however, that higher yields on these instruments came with higher risk, albeit too late for these investors. This study seeks to understand the risk–return tradeoff, managerial skill, and factor exposures on the risk-return tradeoff in two financial instruments that have been limitedly investigated: commodity trading advisors (CTAs) and managed futures funds (MFFs). This study begins by documenting the differences between CTAs/MFFs and hedge funds and mutual funds, starting with the legal and operational differences. Next, it conducts a performance analysis, which indicates that CTAs and MFFs, as standalone investment vehicles, provide returns that are higher than the average market returns in bear markets, while carrying lower risk. The strong standing of CTAs and MFFs in bear markets earn them their reputation as “downside risk protectors.” CTAs and MFFs are profitable individual assets but adding these funds to classical asset portfolios enhances portfolio performance significantly. This feature makes them strong hedging assets. As expected, their performance is below that of standard assets in up markets. Chapter 4 finds that the superior performance of CTAs and MFFs can be explained by managerial skill. Positive and significant Jensen alphas are evidence of good performance; moreover, the persistence of the Jensen alphas is supported by both parametric and non-parametric tests. Incentive fees and fund age are found to be positively related to managerial skill, while (somewhat surprisingly) management fees are found to be negatively related to it. Chapter 5 finds that many financial and macroeconomic factors are statistically unrelated to CTA and MFF performance. However, the value premium (HML) factor and industrial production growth (IPG) are correlated with their performance. HML has a relation effect on one-month-ahead fund returns, whereas IPG has a negative association with them. Nonparametric tests support these results marginally. Overall, these findings suggest that both CTAs and MFFs use well-known and well-established predictors of expected returns to generate their alphas.
Commodity trading advisers, (CTA), or managed futures managers' trade in the commodity market. The hedge funds invest in commodity futures, currencies, bonds and shares. Hedge funds use managed futures in terms of indices, treasuries, fixed-income securities and commodities such as gold, silver, oil, corn, cocoa, sugar etc. Combining managed futures with shares and bonds provide better returns with lower risk or mean variance optimal solution. The optimization is due to the negative or low correlation and better diversification between managed futures and traditional investments such as bonds and shares. Our results suggest that the efficient frontier is achieved by adding managed futures. In other words, we get highest return with low risk. The standard deviation as a measure of risk is reduced and the Sortino ratio, which measures the downside risk, is increased by over 50%. The downside volatility of a mixed portfolio of managed futures, bonds and shares is better represented by the Sortino ratio. The sample is provided from Data Feeder data set. It is very comprehensive and includes managed futures hedge funds for the period 1998 to 2003. The database includes defunct funds and funds that ceased to operate and, therefore, is free from survivorship bias.
"Understanding risk is important. Prior to 2008, as the yields on safe assets hit rock bottom, investors began to focus on an alphabet soup of more complex instruments. These complex securities were rated AAA and appeared as safe as U.S. Treasuries, but with much higher yields. The 2008 financial crisis revealed, however, that higher yields on these instruments came with higher risk, albeit too late for these investors. This study seeks to understand the risk-return tradeoff, managerial skill, and factor exposures on the risk-return tradeoff in two financial instruments that have been limitedly investigated: commodity trading advisors (CTAs) and managed futures funds (MFFs). This study begins by documenting the differences between CTAs/MFFs and hedge funds and mutual funds, starting with the legal and operational differences. Next, it conducts a performance analysis, which indicates that CTAs and MFFs, as standalone investment vehicles, provide returns that are higher than the average market returns in bear markets, while carrying lower risk. The strong standing of CTAs and MFFs in bear markets earn them their reputation as "downside risk protectors." CTAs and MFFs are profitable individual assets but adding these funds to classical asset portfolios enhances portfolio performance significantly. This feature makes them strong hedging assets. As expected, their performance is below that of standard assets in up markets. Chapter 4 finds that the superior performance of CTAs and MFFs can be explained by managerial skill. Positive and significant Jensen alphas are evidence of good performance; moreover, the persistence of the Jensen alphas is supported by both parametric and non-parametric tests. Incentive fees and fund age are found to be positively related to managerial skill, while (somewhat surprisingly) management fees are found to be negatively related to it. Chapter 5 finds that many financial and macroeconomic factors are statistically unrelated to CTA and MFF performance. However, the value premium (HML) factor and industrial production growth (IPG) are correlated with their performance. HML has a relation effect on one-month-ahead fund returns, whereas IPG has a negative association with them. Nonparametric tests support these results marginally. Overall, these findings suggest that both CTAs and MFFs use well-known and well-established predictors of expected returns to generate their alphas"--
Investors face significant barriers in evaluating the performance of hedge funds and commodity trading advisors (CTAs). The only available performance data comes from voluntary reporting to private companies. Funds have incentives to strategically report to these companies, causing these data sets to be severely biased. And, because hedge funds use nonlinear, state-dependent, leveraged strategies, it has proven difficult to determine whether they add value relative to benchmarks. We focus on commodity trading advisors, a subset of hedge funds, and show that during the period 1994-2012 CTA excess returns to investors (i.e., net of fees) averaged 1.8 per cent per annum over US T-bills, which is insignificantly different from zero. We estimate that CTAs on average earned gross excess returns (i.e., before fees) of 6.1%, which implies that funds captured most of their performance through charging fees. Yet, even before fees we find that CTAs display no alpha relative to simple futures strategies that are in the public domain. We argue that CTAs appear to persist as an asset class despite their poor performance, because they face no market discipline based on credible information. Our evidence suggests that investors' experience of poor performance is not common knowledge.
Investors face significant barriers in evaluating the performance of hedge funds and commodity trading advisors (CTAs). The only available performance data comes from voluntary reporting to private companies. Funds have incentives to strategically report to these companies, causing these data sets to be severely biased. And, because hedge funds use nonlinear, state-dependent, leveraged strategies, it has proven difficult to determine whether they add value relative to benchmarks. We focus on commodity trading advisors, a subset of hedge funds, and show that during the period 1994-2007 CTA excess returns to investors (i.e., net of fees) averaged 85 basis points per annum over US T-bills, which is insignificantly different from zero. We estimate that CTAs on average earned gross excess returns (i.e., before fees) of 5.4%, which implies that funds captured most of their performance through charging fees. Yet, even before fees we find that CTAs display no alpha relative to simple futures strategies that are in the public domain. We argue that CTAs appear to persist as an asset class despite their poor performance, because they face no market discipline based on credible information. Our evidence suggests that investors' experience of poor performance is not common knowledge.
Using one of the biggest database ever used in commodity trading advisors (CTA) academic study containing 1892 funds (including 1350 dissolved funds), we investigate CTA performance and persistence in performance in order to determine if some CTA consistently and significantly outperform their peers over various time periods. In order to test the persistence hypothesis, we use a methodology based on Carhart's (1997) decile classification. We also empirically decompose decile's performance across the CTA strategies covered in order to determine if some deciles are more exposed to certain strategies over time. We also analyze the presence of survivorship bias and its evolution over time. We conclude the study in analyzing the dissolution frequencies across deciles and its evolution over time.Keywords: commodity trading advisors, CTA, managed futures, futures, hedge fund, alternative investments, persistence, performance, Carhart, Capocci, Barclay Trading Group, survivorship bias, dissolution frequencies, dissolution, index.
This study investigates performance persistence of Commodity Trading Advisors (CTA) applying a regression-based parametric method in combination with a two-period framework and alpha as a risk-adjusted performance measure. Covering the time period 1995 to 2008, monthly returns of 642 CTAs across five CTA strategies are included in the analysis. To extract alphas, strategy-specific multi-factor models are constructed using stepwise regressions and 25 risk factors, which include equities, bonds, commodities, currencies and option-based factors. In the persistence investigation the alpha of the current period is regressed on the alpha of the previous period with time periods of one, three and six months as well as one and two years examined. The empirical analysis suggests that CTAs have statistically significant exposure to trend following and commodity factors and positive significant alphas. Overall, depending on the estimation method used, there is weak to some evidence for performance persistence. 72% of all significant coefficients of the alpha regressions are negative indicating that performance generally does not persist, but that a period of high (low) alpha tends to be followed by a period of low (high) alpha. While the coefficients for 1-month periods are always insignificant and mostly positive, the coefficients become increasingly significant and negative as the time periods lengthen.
The data and time dependency of empirical financial research is a common concern to both academics and practitioners. Changes in regulatory, trading and investor environments may result in dramatic changes in the underlying viability of any investment vehicle and/or trading process. This is especially true for managed futures programs for which a single commonly used database does not exist and which often are dynamic in nature and are impacted by changes in trading instruments and underlying markets. As a result, empirical analysis of the potential benefits of Managed Futures (e.g., Commodity Trading Advisors (CTAs)) may be impacted by the period of analysis and the strategy composition of the database or index used to represent the managed futures investment. In this analysis, we conduct a series of empirical tests on CTA indices which are designed to represent the overall return to the reporting universe of CTAs (e.g., composite CTA indices). These tests are similar to those previously conducted on a series of 'composite' hedge fund indices (Schneeweis et. al., 2012). Using major composite CTA indices as a surrogate for CTA portfolios, these tests include cross-sectional and time series analysis. Results reflect the common wisdom that performance results may be dominated by the period of analysis as well as the index and multi-factor regression model used.
Commodity markets have gained a lot of momentum in the past decade. Some commodity fund managers or commodity trading advisors (CTA) have seen this trend emerge in the early 1980ies. They have developed so-called systematic trend following strategies to rake in huge profits for their investors. Today, about 180 billion USD are managed by CTAs. Even though this sounds like a lot of money, CTAs only account for 4.4% of the multi trillion USD hedge fund industry. However for diversification reasons, CTAs have seen rapidly increasing demand in the past fifteen years. As of the third quarter of 2007 the assets under management in CTAs have increased by a factor of three since 2000 and a factor of nine since 1990. For investors though, who would like to invest in CTAs, it is challenging to find out what commodities a CTA really trades because of the limited transparency of such funds. The thesis at hand aims to contribute to this issue by analysing a sample of thirty-eight CTAs with the help of the principal components analysis and the style analysis.