BestEx Research Launches Pre-Trade Analytics

Transaction cost analysis provider BestEx Research has launched Pulse Analytics, a new product offering pre-trade and execution analytics.

The new platform is an API-first system that is accessible via a REST API or the firm’s cloud-based front end, and will initially offer analytics on futures products across FX, energy, equities, interest rates, metals and agri products.

The symbol-specific transaction cost estimates reflect the unique structural nuances of futures markets, the firm says, adding the model provides both historical and forward-looking transaction cost estimates, broken down into market impact and order placement cost components. Estimates account for key factors affecting execution cost, such as order size, urgency, duration, and time of day.

In addition to cost estimates, the model provides access to other execution-relevant analytics – including trade imbalance, spread, and depth of book – as well as benchmark prices such as VWAP, participation-weighted price (PWP), and arrival price. These capabilities enable institutional traders to back-test strategies with cost awareness, evaluate historical trading costs, and estimate the cost of future trading.

“Today’s trading analytics are often delivered as static PDFs or black-box GUIs, but we believe that model is outdated,” says Hitesh Mittal, founder and CEO of BestEx Research. “The future is API-driven, because portfolio managers and traders want tools they can integrate directly into their workflows, connect to AI engines, or use to build their own dashboards. An API-first approach raises the bar for robustness and transparency–clients want to understand how models work in order to trust and adapt them. That’s why we built Pulse Analytics, a platform that reflects how trading and technology are evolving.”

Adam Orlov, COO of Aura Capital, has been a beta user of the Pulse Market Impact Model, and says, “With the recent uptick in volatility across products, getting a handle on trading costs has been a real focus for us. It’s not something you solve overnight, but having a reliable model that can be plugged in via API – and used to run multiple cost iterations across order size, duration, and participation – has allowed us to factor cost into position sizing and portfolio construction in a way we couldn’t before. It’s helped us avoid situations where trades look good on paper but give back too much in execution. That’s been really impactful.”