In this research note, we examine the performance differences among three distinct systematic methods for managing notional and risk exposure of individual positions in a representative trend-following strategy.

The simplest method, for a given signal level, maintains a constant initial number of contracts throughout the life of a trade, while the other two models dynamically adjust the number of contracts to achieve a constant notional exposure or a constant risk exposure (or dynamic volatility- based position sizing), respectively.

We begin with a straightforward illustrative example – a single trade capturing the surge in cocoa futures prices between 2023 and 2024 – to illustrate how different position sizing methodologies can lead to drastically different outcomes based on an identical signal. However, when analyzing return distributions across a sample of 2,750 trades spanning 50 markets over the past 30 years, we observe minimal differences in average returns among the three models, with notable distinctions appearing only in the top 25% of the winning trades.

We show that, compared to a static approach, dynamically scaling market exposure inversely to volatility has no impact, positive or negative, on the risk-return profile of losing trades. However, it does enhance the risk- adjusted return profile of the quartile of most profitable trades – albeit at the cost of capping absolute per-trade returns. This result is supported by a pattern observed in the change in market volatility across the lifecycle of the 25% most profitable trades (which is not seen across the sample of losing trades), where volatility is 1.4 times higher on average during their lifetime compared to entry, acting as a take-profit mechanism.

Our analysis reveals that a more concentrated risk approach (i.e., not adjusting exposure to changing market conditions) does not lead to superior long-term risk-adjusted returns. While the difference can be significant on a trade-by-trade basis, particularly for the most profitable trades, the impact of dynamically managing individual position exposures on the long-term performance of a trend-following strategy is surprisingly limited. Nevertheless, the results suggest that dynamically adjusting exposures inversely to market volatility offers the best balance between managing portfolio concentration risk and optimizing long-term performance. While it may limit individual trade profits, it prevents excessive concentration and reduces the risk of large losses from a single position, all without sacrificing overall strategy risk-adjusted returns.