Trading Advisors Research Articles

Testing Futures Trading Strategies: How Robust are Standard Assumptions?

There is a growing literature examining futures based trading strategies and the performance of Commodity Trading Advisors (CTAs). In this paper, we test the validity of three key assumptions used in these studies. The validity of basing conclusions on analysis of synthetic rather than market price data is tested. We review the evidence on the level of transaction costs to test the cost model used in modelling futures based trading strategy. Finally, we test the assumption that CTAs generally charge a management fee of 2% and incentive (performance) fee of 20%. In addition, the trend over time in the structure of fees is presented. Our findings suggest that inferences based upon synthetic futures replicate those based on exchange-traded data. Over the full period, the average fee levels were measured at 1.82% (management) and 20.2% (incentive) close to and not significantly different from the levels used in the literature.

Practical Applications of The Moral Hazard Problem in Hedge Funds: A Study of Commodity Trading Advisors

<h3>Practical Applications Summary</h3> Research shows that poorly performing hedge funds tend to engage in risk-shifting behavior—increasing volatility—to boost returns and, in turn, performance fees, especially when fee structures contain triggers such as high-water marks. In <b>The Moral Hazard Problem in Hedge Funds: <i>A Study of Commodity Trading Advisors</i></b>, <b>Li Cai</b>, <b>Chris (Cheng) Jiang</b>, and <b>Marat Molyboga</b> demonstrate that the market environment affects risk-shifting behavior among hedge funds—less risk-shifting behavior occurs in unfavorable market environments, and vice versa. The study also provides new evidence linking investment strategy and risk choices. The authors find that although risk-shifting behavior can increase fees for managers, it lowers investors9 risk-adjusted returns.

Implementing and testing the Maximum Drawdown at Risk

Financial managers are mainly concerned about long lasting accumulated large losses which may lead to massive money withdrawals. To assess this risk feeling we compute the Maximum Drawdown, the largest price loss of an investment during some fixed time period. The Maximum Drawdown at Risk has become an important risk measure for commodity trading advisors, hedge funds managers, and regulators. In this study we propose an estimation methodology based on Monte Carlo simulations and empirically validate the procedure using international stock indices. We find that this tool provides more accurate market risk control and may be used to manage portfolio exposure, being useful to practitioners and financial analysts.

Performance, Persistence, and Pay: A New Perspective on CTAs

Using a large and representative dataset of commodity trading advisors (CTAs), we provide compelling evidence that CTAs generate significant net excess returns of at least 4.1% annually; that approximately 64% of the funds have positively skewed returns; and that there is considerable heterogeneity amongst CTAs, with systematic trend followers doing significantly better than other subcategories. More importantly, we find that CTAs not only beat passive, normative benchmarks, with a yearly gross alpha of at least 5.3% but also generate significant, incremental crisis alpha during periods of equity market turmoil. Finally, we show that cross-sectional differences in the performance of CTAs are persistent up to 3 years and that managerial compensation predicts fund performance. Our results are consistent with a rational market where investors compete to invest with successful CTA managers, who use fees to signal their skills to investors.

The Moral Hazard Problem in Hedge Funds: A Study of Commodity Trading Advisors

The asymmetric nature of performance-based compensation in hedge funds introduces a moral hazard problem in which investors bear the negative consequences of fund managers’ risk choices. In this article, the authors analyze whether risk shifting by a hedge fund manager is related to the manager’s investment strategy and survivorship concerns. Using gross fund returns from 1994 to 2014, the authors find that the tendency to increase risk following poor performance is weak (strong) when there are strong (weak) managerial survivorship concerns. At the same time, risk shifting is significantly less prevalent when a manager uses algorithms, instead of discretion, in an investment strategy. The authors introduce a new model for estimating the economic impact of risk shifting on hedge fund managers and investors. They estimate that fund managers generate an additional 0.25% per annum in fees that negatively impact investors’ risk-adjusted returns.

Duration Dependence, Behavioral Restrictions, and the Market Timing Ability of Commodity Trading Advisors

AbstractThis paper addresses a potential shortcoming in the work on the market timing ability of fund managers. We adapt the Henriksson‐Merton (1981) test for market timing by relaxing a behavioral assumption that is implicit in the use of daily data. To this end, we relax the assumption that managers base their market timing decisions on daily excess returns. Instead, we use results from the literature on bull and bear markets and test whether fund managers can successfully time such trends in financial markets. We make use of a proprietary dataset of daily Commodity Trading Advisors (CTAs) returns to show that CTAs, on average, are able to time the bull and bear markets we identify.

Tail protection for long investors: trend convexity at work

The performance of trend-following strategies can be ascribed to the difference between long- and short-term realized variance. We revisit this general result and show that it holds for various definitions of trend strategies. This explains the positive convexity of the aggregate performance of commodity trading advisors, which, when adequately measured, turns out to be much stronger than anticipated. We also highlight interesting connections with so-called risk parity portfolios. Finally, we propose a new portfolio of strangle options that provides a pure exposure to the long-term variance of the underlying, offering yet another viewpoint on the link between trend and volatility.

The profiles of merged hedge funds, funds of hedge funds, and CTA

This study examines the profiles of 412 merged hedge funds (HFs), funds of HFs (FoHFs), and commodity trading advisors (CTAs) over the January 1994 through December 2013 period. We find that merged HFs, FoHFs, and CTAs are typically younger than live HFs but older than dead funds. We also find that merged HFs, FoHFs, and CTAs have relatively fewer constraints than live and dead ones. Specifically, they have shorter lockup period, use less leverage and request less value of purchasing initial investments or units. In addition, we find that past performance is a significant determinant for mergers. Thus, HF, FoHF, and CTA mergers could be motivated by a need to eradicate bad performing funds. These results are robust to different performance measures and hold after correcting for backfill bias and removing the effects of artificial serial correlation.

Tail Protection for Long Investors: Trend Convexity at Work

The performance of trend following strategies can be ascribed to the difference between long-term and short-term realized variance. We revisit this general result and show that it holds for various definitions of trend strategies. This explains the positive convexity of the aggregate performance of Commodity Trading Advisors (CTAs) which -- when adequately measured -- turns out to be much stronger than anticipated. We also highlight interesting connections with so-called Risk Parity portfolios. Finally, we propose a new portfolio of strangle options that provides a pure exposure to the long-term variance of the underlying, offering yet another viewpoint on the link between trend and volatility.

Dynamic dependence networks: Financial time series forecasting and portfolio decisions

We discuss Bayesian forecasting of increasingly high‐dimensional time series, a key area of application of stochastic dynamic models in the financial industry and allied areas of business. Novel state‐space models characterizing sparse patterns of dependence among multiple time series extend existing multivariate volatility models to enable scaling to higher numbers of individual time series. The theory of these dynamic dependence network models shows how the individual series can be decoupled for sequential analysis and then recoupled for applied forecasting and decision analysis. Decoupling allows fast, efficient analysis of each of the series in individual univariate models that are linked – for later recoupling – through a theoretical multivariate volatility structure defined by a sparse underlying graphical model. Computational advances are especially significant in connection with model uncertainty about the sparsity patterns among series that define this graphical model; Bayesian model averaging using discounting of historical information builds substantially on this computational advance. An extensive, detailed case study showcases the use of these models and the improvements in forecasting and financial portfolio investment decisions that are achievable. Using a long series of daily international currencies, stock indices and commodity prices, the case study includes evaluations of multi‐day forecasts and Bayesian portfolio analysis with a variety of practical utility functions, as well as comparisons against commodity trading advisor benchmarks. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Risk Shifting or Just Risk-Adjusted Returns

Intuitively, option-like compensation contracts induce risk-shifting behavior, confirmed by numerous empirical studies. However, theoretical work has shown that risk shifting should not happen without a definite expiration date of the option. With a sample of Commodity Trading Advisors (CTAs), we show that increases in risk (interpreted as risk shifting) correspond to even greater increases in return, as shown by increasing Sharpe ratios. Second, controlling for expected returns eliminates measured risk shifting. Finally, measured risk shifting behavior, strong between 1994 and 2003, is substantially lower or missing from 2004 to 2014. Thus, we conclude that CTAs are increasing risk adjusted returns, not risk shifting, confirming the theoretical results.

A Liquid and Investable Benchmark Index for the Commodity Trading Advisor and Managed Futures Industry

In 2014 and 2015, we surveyed investors and managers and asked the question, “Commodity trading advisors (CTAs)—How do they do it?” The survey responses allow us to explain the complexity of the CTA and managed futures industry with a simple, survey-led index model of trading global liquid markets with momentum indicators in a risk-weighted basket, managed to a target volatility and charging 2/20. This article first presents the survey results and the index construction. It then discusses how well the index represents the CTA industry. Finally, it discusses the benefits and application of the J8 CTA Index.

What Are the Sources of Return for CTAs and Commodity Indexes? A Brief Survey of Relevant Research

This survey article discusses the (potential) structural sources of return for both commodity trading advisors and commodity indices based on a review of empirical research from both academics and practitioners. The article specifically covers (1) the long-term return sources for both managed futures programs and for commodity indices, (2) the investor expectations and the portfolio context for futures strategies, and (3) how to benchmark these strategies. <b>TOPICS:</b>Commodities, futures and forward contracts, performance measurement

Preparing Financial Regulation for the Second Machine Age: The Need for Oversight of Digital Intermediaries in the Futures Markets

Humanity is entering the Second Machine Age, in which artificially intelligent computers and software programs (artificial agents) will become involved in almost every aspect of society. Computers and software programs now drive and park cars, fly drones, compose music, sell insurance, manage investments, and even write news stories. Indeed, computers and software programs are far better––and quicker––than humans at jobs that involve looking at numbers and drawing conclusions from them, which would include jobs such as investment advisors and futures traders. The rise of automated trading systems (“ATSs”) that use high-frequency trading strategies in the futures markets is but one example of how technology is fundamentally changing the nature of the financial markets. As a result, humans who are operating as futures market intermediaries (such as commodity trading advisors or introducing brokers) are likely to be displaced by digital intermediaries, that is, artificial agents that perform critical roles related to enabling customers to access the futures and derivatives markets. The Commodity Exchange Act (“CEA”) governs the U.S. derivatives markets and requires specified categories of intermediaries––such as commodity trading advisors (persons who are compensated to give advice about derivatives)––to register with the Commodity Futures Trading Commission (“CFTC”). Compulsory registration has been called “the kingpin” of the CEA’s “statutory machinery” because it serves to identify the persons acting as market professionals, and provides a mechanism for such persons to undergo background screenings for fitness to work in the industry, as well as proficiency testing and ethics training. Because technological advances are enabling artificial agents to perform many of the intermediary roles that previously were done by humans, Congress and the CFTC should modify the CEA and CFTC Regulations (1) to expand the scope of persons who must register to include, inter alia, persons who use ATSs and who have trading privileges on, or direct electronic access to, derivatives exchanges (or trading venues), and (2) to implement an identification program for ATSs and algorithms. Lastly, Congress and the CFTC should consider proposals in research by academics in philosophy and law concerning (1) ways to ensure that digital intermediaries are built not just to be intelligent but also to be ethical, and (2) methods for allocating liability for wrongdoing by digital intermediaries.

Factors affecting the birth and fund flows of CTAs

Our paper investigates the timing of the inception of commodity trading advisors and the relationship between their fund flows and performance. Our results show that commodity trading advisor industry performance has, over the long-run (short-run), a positive (negative) effect on new commodity trading advisors. The functional form of the flow-performance relation varies across commodity trading advisor subcategories. Also, we do not observe a ‘smart money’ effect, indicating that investors are generally unsuccessful in choosing subsequent high-performing commodity trading advisors.

Common Denominators in the Commodity Trading Advisor and Managed Futures Industry: A Survey Report

How do commodity trading advisors (CTAs) generate returns? Which markets do they trade? How do they allocate risk, manage money, and what fees do they charge? We conducted an international survey to establish common denominators in the CTA and managed futures industry. This article presents the results and conclusions from the survey. The survey finds that the CTA and managed futures industry may be generalized in trading popular key global markets in a risk-weighted momentum portfolio managed to a target volatility and applying a 2/20 fee structure.

Commodity Trading Advisor Indexes And Alpha Generation Relationships

This research investigates the trend following relationships between Commodity Trading Advisor (CTA) Indexes and a widely known trend following proxy Index using a database covering 21 years with 24 CTA, Managed Futures, and Hedge Fund (that can trade CTA-like) Indexes. The trend following relationships are tested using a modification of the Methodology employed by Baesel, Gonzalez-Heres, Chen, &amp; Shin (2012). A unique Alpha adjustment is proposed to include the traditional Alpha plus or minus a reward or penalty for displaying relationships to the larger positive and negative returns of the trend following Index proxy. Results for the first sample period show evidence of at least some association of the returns of the trend following proxy to those of the individual CTA Indexes; however, most of the Indexes showed little to no statistical support for much traditional or adjusted Total Alpha generation. For the second sample period the regression results show that almost none of the Indexes had a statistically significant association with the monthly total returns of the trend following proxy Index. Instead, generally all of the Indexes showed the impact of the larger monthly returns of the trend following proxy Index such that the Alpha adjustments overall were positive and, on average, generated approximately 50% of the Total Alpha of the individual CTA Indexes.

A Generalized Stepwise Procedure with Improved Power for Multiple Inequalities Testing

We propose a stepwise test, Step-SPA(⁠k⁠), for multiple inequalities testing. This test is analogous to the Step-SPA test of Hsu, Hsu, and Kuan (2010, J. Empirical Econ., 17, 471–484) but has asymptotic control of a generalized familywise error rate: the probability of at least k false rejections. This test improves Step-RC(⁠k⁠) of Romano and Wolf (2007, Ann. Stat., 35, 1378–1408) by avoiding the least favorable configuration used in Step-RC(⁠k⁠). We show that the proposed Step-SPA(⁠k⁠) test is consistent and more powerful than Step-RC(⁠k⁠) under any power notion defined in Romano and Wolf (2005, Econometrica, 73, 1237–1282). An empirical study on Commodity Trading Advisor fund performance is then provided to illustrate the Step-SPA(⁠k⁠) test. Finally, we extend Step-SPA(⁠k⁠) to a procedure that asymptotically controls the false discovery proportion, the ratio of the number of false rejections over the number of total rejections, and show that it is more powerful than the corresponding procedure proposed by Romano and Wolf (2007, Ann. Stat., 35, 1378–1408).

Style Selection and U.S. Investors’ Risk Appetite

The authors believe that the prevailing Treasury term structure gives important information about the desired investment time horizon of investors. They equate this time horizon to the implied duration of liabilities of a representative investor and estimate this target duration over the post-war period using monthly zero coupon yield-curve data provided by the U.S. Federal Reserve. In their view, mismatches between actual and target duration provide a measure of risk appetite. The authors test this hypothesis with a simple model that uses target duration to predict periods of outperformance of U.S. stocks over U.S. Treasury bonds and hedge funds over CTAs (commodity trading advisors). The model generates attractive risk-adjusted returns with minimal parameterization. <b>TOPICS:</b>Fixed income and structured finance, performance measurement

Fooling Some of the People All of the Time: The Inefficient Performance and Persistence of Commodity Trading Advisors

Investors face significant barriers in evaluating the performance of investment advisors. We focus on commodity trading advisors (CTAs) and show that from 1994 to 2012, CTA excess returns to investors (i.e., net of fees) were insignificantly different from zero while gross excess returns (i.e., before fees) were 6.1%, which implies that managers captured the performance in fees. Moreover, we find that CTAs display no alpha relative to simple future strategies in the public domain. Our results have implications for all hedge fund studies in that we find the typical adjustments for biases in the hedge fund databases still leave upward bias in fund performance.