Performance, Managerial Skill, and Factor Exposures in Commodity Trading Advisors and Managed Futures Funds

Performance, Managerial Skill, and Factor Exposures in Commodity Trading Advisors and Managed Futures Funds

by S. Burcu Avci


View All Available Formats & Editions
Members save with free shipping everyday! 
See details


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.

Product Details

ISBN-13: 9781612334738
Publication date: 11/15/2019
Pages: 156
Product dimensions: 6.14(w) x 9.21(h) x 0.33(d)

Table of Contents

List of Tables vii

List of Figure xi

Abstract xiii

List of Abbreviations xv

CHAPTER 1: Introduction 1

1.1 Industry Overview 5

1.1.1 Mutual Funds Industry 7

1.1.2 Hedge Fund Industry 11

1.1.3 Managed Futures Industry 13

1.1.4 Similarities and Differences among Managed Futures,

Mutual Funds, and Hedge Funds 17

1.1.5 Regulation in Financial Services Industry 21

1.2 Literature Review 24

1.2.1 Performance Analysis of Managed Futures Funds 24

1.2.2 Managerial Skill and Persistence 27

1.2.3 Predictability of Future Returns 32

CHAPTER 2: Data and Summary Statistics 37

2.1 Potential Data Biases 50

2.1.1 Survivorship Bias 50

2.1.2 Backfill Bias 51

2.1.3 Selection Bias 53

2.1.4 Multi-period Sampling Bias 54

CHAPTER 3: Performance Analysis 55

3.1 CTAs and MFFs as Standalone Investment Vehicles 55

3.1.1 Sharpe Ratio Ranking of Funds 57

3.1.2 Roy’s Criterion Ranking of Funds 57

3.1.3 Kataoka’s Criterion Ranking of Funds 58

3.1.4 Sortino Ratio Ranking of Funds 59

3.2 CTAs and MFFs as Portfolio Assets 63

3.2.1 Optimization with Respect to Sharpe Ratio 63

3.2.2 Optimization with Respect to Roy’s Criterion 66

3.2.3 Optimization with Respect to Kataoka’s Criterion 67

3.2.4 Optimization with Respect to Sortino Ratio 69

3.3 Bull and Bear Market Analysis 69

CHAPTER 4: Managerial Skill 77

4.1 Jensen Alphas 77

4.2 Persistency 86

4.3 Fund Flows 90

CHAPTER 5: Factor Exposures to CTAs and MFFs 97

5.1 Parametric Tests 98

5.1.1 Univariate Fama–MacBeth Regressions 98

5.1.2 Multivariate Fama–MacBeth Regressions 106

5.1.3 Multivariate Fama–MacBeth Regressions

Using Control Variables 107

5.2 Nonparametric Tests 109

5.2.1 Univariate Portfolio Analysis 110

5.2.2 Bivariate Portfolio Analysis 118

CHAPTER 6: Conclusion 127

References 129

Customer Reviews