A superhuman edge on trading analytics

The Pulse Market Impact Model returns transaction cost estimates for a given order specific to the instrument, order size, and order duration. It is accessible via REST API and our Algorithm Management System (AMS), which offers a point-and-click user interface.

Unlike traditional models that rely on equity-centric assumptions, Pulse is designed to account for the unique microstructure complexities of each asset class. It partitions total cost into market impact and order placement cost components, yielding more actionable estimates. The model is currently live for Global Futures, with cost estimates for Equities coming soon.

While market impact exists in all traded instruments, futures present unique modeling challenges that must be accommodated for more accurate cost estimation. Unlike equities, futures often have wider tick sizes, thinner order books, and more volatile liquidity conditions — especially around macro events and roll periods. With a thoughtful, futures-specific approach, these structural differences can be well accounted for in cost estimates.

Shadow liquidity refers to the hidden capacity of the market—the volume that exists beyond visible top-of-book orders. In futures, where displayed liquidity can be sparse or fleeting, accounting for this hidden layer is critical. Ignoring it can lead to poor slippage estimates and misinformed execution decisions. Pulse accounts for shadow liquidity by following a unique normalization approach and building a separate model for each base symbol, capturing its unique liquidity profile.

In large-tick futures—such as many short-duration interest rate contracts, for example—prices move in coarse increments, leading to artificially wide spreads and clustered prints. This distorts traditional impact models, which assume more continuous price behavior. Pulse normalizes model inputs and cost differently to support more accurate estimates under large-tick conditions.

Yes. Rather than grouping instruments by volume or volatility, Pulse contains distinct models for each base symbol and accounts for each symbol’s unique liquidity profile. This allows the model to adapt naturally across the liquidity spectrum—capturing hidden liquidity in illiquid instruments and preventing overfitting in highly liquid ones.

Pulse is available via API and our Algorithm Management System (AMS). Our team provides onboarding support and training to all of our clients as needed. To request access, institutional investors can contact us directly or request a free trial using the button below.

Pulse has been validated against over 70,000 executed orders from BestEx Research algorithms, covering a wide range of products, order sizes and durations, and market conditions. Pulse’s estimates align with out-of-sample data, confirming its stability over time, contract expiries, and execution speeds. Some of these results are shown in the performance section above. For a deeper look at our testing methodology and results, request access to the Pulse research paper.

We offer trial access for qualified users interested in exploring Pulse’s capability. To get started, use the “Request Access” link below or contact our team directly.