Built to Scale – A Structural Look at DBi’s Approach
Executive Summary
The capacity of a strategy is an important question in asset management, often tied to the strategy’s ability to scale without materially impacting returns. Investment strategies, whether in private or public markets, encounter diminishing alpha as assets under management (AUM) grow. However, not all strategies are equally capacity constrained. In this paper, we will outline how our research shows that conventional fund capacity limitations have minimal impact on DBi strategies, and why scaling does not impair the opportunity set.
Key Considerations
Regulatory Limits
A common constraint for funds which invest in futures markets comes from exchange-imposed position limits, which are hard caps that restrict how many contracts a single entity can hold in a given futures market. For many large-scale trading strategies, particularly those with concentrated directional exposures or heavy reliance on niche contracts, these caps are the primary factor restricting capacity.
Hard position limits in contracts like Live Cattle or Lumber impose strict ceilings on the number of contracts a single participant can hold, regardless of their capital base or trading rationale. For a large fund, these caps can quickly become binding capacity constraints. For example, in Live Cattle, the hard cap of ~6,300 contracts translates to roughly $550 million notional exposure1. Once a fund reaches that position size, it cannot add more risk without breaching exchange rules. This forces portfolio managers to scale back, spread risk into less optimal instruments, or avoid building meaningful exposure in these markets altogether. The result is that such hard-capped products are often impractical for larger funds, even if the market opportunity is attractive, because regulatory limits prevent deploying capital at scale.
By contrast, the contracts DBi utilizes are governed not by hard caps but by reporting thresholds. Reporting allows for much greater flexibility: once a threshold is reached, the exchange may request justification, but does not impose a hard limit on positioning. As a result, DBi is not constrained by regulatory position limits and can continue to build and scale positions as AUM grows.
Liquidity
Shadow Liquidity
When assessing the scalability of a trading strategy, especially one that operates in futures markets, traditional measures of liquidity such as ADV or visible order book depth often provide an incomplete picture. Shadow liquidity refers to the hidden or off-screen liquidity that exists beyond the volume in the futures market itself. Shadow liquidity is important for futures contracts which do not have a reference benchmark.
For example, cattle futures typically exhibit higher on-screen trading volume than S&P 400 MidCap futures, this does not necessarily imply greater true liquidity. While cattle contracts are actively traded, with tight bid/ask spreads in the front months, they lack a standardized reference index, which limits the ability of market makers or institutions to hedge or arbitrage effectively. In contrast, S&P 400 MidCap futures, though less actively traded on screen, are tied to a well-defined benchmark index and are supported by a broader ecosystem of liquidity providers. Institutions can price and hedge these futures against ETFs, index baskets, and swaps, allowing for arbitrage strategies and off-screen liquidity. This structural support creates a hidden layer of liquidity that can absorb larger trades with less slippage, even if it’s not reflected in visible volume.
Instruments without a reference benchmark can also exhibit substantial shadow liquidity when there is active arbitrage with related markets. This liquidity is not always visible on-screen but emerges through dynamic linkages with spot, ETF, swap, and forward markets. Take the Australian dollar contract as an example: while it may trade around $5 billion in average daily futures volume, the broader ecosystem, including spot FX, forwards, swaps, and ETFs, supports an estimated $155 billion in total effective liquidity. This cross-market depth allows for execution of large futures positions with less slippage than visible volume would suggest, demonstrating that benchmark-linked pricing isn’t the only path to meaningful off-screen liquidity in futures. The table below presents the estimated daily trading volume of linked markets for deliverable futures for which DBi trades.
Transaction Costs
Liquidity examines the potential scale at which a strategy can operate, but accessing it efficiently is only part of the equation. The real-world cost of interacting with this liquidity particularly as order sizes grow brings transaction costs into focus. Even in highly liquid markets like futures, the manner in which trades are executed can significantly influence realized performance. As a strategy scales, transaction costs become a more prominent consideration. DBi partners with BestEx Research (BER) to give investors access to advanced trading algorithms that minimize implicit costs. After a two-year evaluation of competing solutions in which each algorithm targeted the settlement price, DBi found that BER’s algorithms delivered positive trading alpha versus the two next-best alternatives, and more than 90 basis points annually relative to settlement prices.
Conclusion
Fund capacity is a critical consideration in asset management, particularly for strategies whose alpha degrades as assets grow, such as statistical arbitrage, discretionary macro, or capacity-constrained CTAs. DBi’s approach is fundamentally different. The alpha is not derived from short-lived inefficiencies or directional forecasting, but from fee disintermediation by systematically replicating core hedge fund exposures through highly liquid futures contracts. In doing so, we advance our goal to deliver hedge fund like returns with significantly lower cost.
While the precise capacity of any futures-based strategy is difficult to define, especially given the role of shadow liquidity and cross-market depth, we are confident that the capacity of DBi’s strategies is substantially higher. This confidence is grounded not only in theory, but in practice. Unlike traditional CTAs, DBi’s strategies do not require holding hundreds of different markets or forecasting marginal price movements. Instead, we focus on liquid exposures where structural liquidity is both deep and resilient.
Importantly, capacity is not a static metric, it requires ongoing diligence. At DBi, we continuously research and monitor trading impact, market structure, and execution performance to ensure that no degradation occurs as assets grow. This includes systematic reviews of fill quality, slippage versus benchmarks, and observed versus expected market impact.
DBi has carefully struck a balance between selecting factors that are relevant for replication and ensuring the underlying instruments offer sufficient liquidity to support scalable execution. As assets under management scale, DBi’s strategies continue to operate efficiently across the same core instruments, preserving both performance and the investor experience.
1 CME Position Limits and Reportable Levels.
Gold estimated by World Gold Council. Link here.
SOFR estimated using CME and OFR.
Treasury interest rates estimated using CME futures volume, SIFMA and Treasury TRACE reports, and applying a proxy multiplier using SOFR for other instruments. Link here.
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