In this research note, we analyze the relationship between the optimal size of an investment universe, its investment capacity, and the underlying market liquidity characteristics for a typical medium-term trend-following strategy, using commodities as a case study.
For most trend-following CTAs, commodities are a key part of their investment universe and can be a key contributor to performance. In fact, over the past five years, we estimate that commodities may have contributed approximately half of the trend-following CTA industry's total returns through December 2024. Among all asset classes, commodity futures present the broadest and most diverse range of investment opportunities for trend-followers as evidenced by their historically lower average cross-correlations in trend-following returns.
While commodities present on paper substantial diversification benefits, we find that these benefits are heavily influenced by the liquidity available in each commodity market. While we do not find any clear relationship between market liquidity and the historical profitability of trend-following after accounting for trading costs, we show that less liquid markets tend to exhibit weaker trend-following return correlations, while more liquid markets appear more strongly correlated. As a result, the expected theoretical Sharpe ratio of a broadly diversified trend-following strategy across 69 commodity markets can be nearly twice as high as that of a universe restricted to only the 10 most liquid commodity markets.
In practice, however, it is difficult to fully capitalize on these diversification benefits due to inherent market capacity constraints. Commodity futures liquidity is highly concentrated: out of a universe of 69 commodity futures, the 10 most liquid commodity markets account for approximately 70% of the total liquidity across all available commodity futures, with energy futures alone accounting for 55-65%. As the target investment capacity of a strategy increases, risk allocation must shift toward more liquid markets, leading to higher return correlations and hence a decline in the strategy’s expected Sharpe ratio.
For a $1 billion target capacity for the commodity allocation in a medium-term trend-following program (corresponding to an approximately $3-4 billion capacity for the fully diversified program), the more concentrated risk allocation amongst fewer instruments can result in an estimated 17% Sharpe ratio deterioration, equivalent to an estimated -1.6% annual drag on returns (assuming a 12% p.a. target portfolio volatility), compared to the unconstrained case.
Additionally, the average historical per-market Sharpe ratio across a full universe of 69 commodity futures is around 0.15-0.2, fluctuating within a narrower range of approximately ±0.1. As the risk allocation is concentrated in fewer markets, confidence in this number decreases, driven by the substantial dispersion in trend-following Sharpe ratios across markets, leading to greater variability in expected performance.
At the same time, our framework, built on our proprietary liquidity models, underscores the potential opportunity cost of trading fewer markets than the capital allocated to a strategy would theoretically permit. For example, trendfollowing ETFs, which have recently gained popularity due to their lower fees and ease of access, are structurally limited to trading only a fraction of the markets available to an unconstrained CTA. As a result of the lack of full diversification potential, the expected structural drag on performance can be as high as 4% per year before fees over the long term. This drag can potentially negate or even outweigh the benefits of lower fees when compared to more expensive, yet better-diversified implementations with more effective use of their investment capacity.
We conclude that the optimal number of commodity markets traded in a trend-following program is directly tied to its target investment capacity. Understanding and carefully evaluating the relationships between diversification benefits, implementation costs and investment capacity is essential to selecting an optimal investment universe that maximizes the performance potential of a trend-following strategy.