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External Research – Managed Futures

On this page, we present various interesting research articles for Managed Futures / CTA strategies. Most of them are focused on trend-following strategies.

Trend Following

Time-Series Momentum: Is It There?

Dashan Huang, Jiangyuan Li, Liyao Wang, Guofu Zhou: Time series momentum (TSM) refers to the predictability of the past 12-month return on the next one-month return and is the focus of several recent influential studies. This paper shows that asset by-asset time series regressions reveal little evidence of TSM, both in- and out-of-sample. While the t-statistic in a pooled regression appears large, it is not statistically reliable as it is less than the
critical values of parametric and nonparametric bootstraps. From an investment perspective, the TSM strategy is profitable, but its performance is virtually the same as that of a similar strategy that is based on historical sample mean and does not require predictability. Overall, the evidence on TSM is weak, particularly for the large cross section of assets. Download the paper here:

When It Pays to Follow the Crowd: Strategy Conformity and CTA Performance

Nicolas P.B. Bollen, Mark C. Hutchinson, John O’Brien: Prior research in hedge fund and mutual fund management finds a positive relation between portfolio distinctiveness and subsequent performance, suggesting that strategy differentiation is associated with superior skill. We find that CTAs with returns that correlate more strongly with those of peers feature higher performance and are more highly exposed to a time series momentum factor. In contrast to hedge funds and mutual funds, CTA strategy conformity appears to be a signal of managerial skill. These results indicate that a common trend following strategy drives CTA returns and that CTAs offer investors an opportunity to invest in momentum.
Download the paper here:

You Can’t Always Trend When You Want

AQR: (Abhilash Babu, Brendan Hoffman, Ari Levine, Yao Hua Ooi, Sarah Schroeder, Erik Stamelos): We present a novel framework to decompose the drivers of trend-following performance into (i) the magnitude of market moves, (ii) the strategy’s ability to profit from those market moves, and (iii) the degree of diversification across markets. This framework allows us to examine why trend performance has been below the strategy’s long-term average return during the current decade. We find that the lower performance of the strategy is neither explained by (ii) nor (iii): trend following has continued to profit from market moves and benefit from diversification. Instead, the primary explanatory factor is (i), namely that the average size of global market moves has been more muted than usual in the current decade. The fact that trend-following strategies continue to translate market moves into profits in a diversified manner suggests that trend-following investing may see stronger performance in market environments characterized by more pronounced movements in markets going forward. Download the paper here:

Are Small CTA Funds Better than Large Ones?

CTAs have been particularly successful in the 2008 crisis and this has resulted in a concentration of the industry. But is large better? Although CTA is known to be a very liquid strategy, large funds face some side effects. Although statistical evidence supporting the hypothesis of an over-performance of small funds over large ones is not strong, rational arguments have been put forward: the inability to diversify across a large universe of future contracts due to limited liquidity in selected markets, especially the commodity market, and the increased slippage and market impact due to increased order sizes. This article empirically looks at the question of whether large inflows force managers to change the investment universe of managed futures strategies, finally reducing their exposure to less liquid asset classes. Interestingly, we do not detect a change of allocation to the commodity asset class by large or by small managed future hedge funds. This result seems to praise the research efforts done in large programs using sophisticated optimization tools to exploit the correlation across assets leading to the conclusion that large CTA funds appear to cope well with their size.