Simulating market execution for banks: accurately forecast market impact of every trade
Achieving best execution for banks
Dynamically AB test pre-trade market slippage and TCA in real-time.
What if you could discover the best parameters for your trades and visualize market slippage before going live, or find out how much it is going to cost you to trade?
With Simudyne’s high-fidelity, agent-based market simulator, this is now a reality.
Use our feature-rich simulation environment to generate realistic market conditions. Dramatically reduce the amount of AB testing of possible strategies; counterfactually see what would happen if you’d tried different parameters and which one would work best in a certain market condition.
Take the risk out of the market and into agent-based simulation with a more robust method of estimating transaction costs and ensuring best execution.
Forecast market slippage
Discover the best parameters for your trade and assess the impact before going live.
Reveal realistic outcomes
Reveal realistic outcomes under varying execution parameters and market conditions—such as fire sales and exogenous market shocks.
Understand pre-trade TCA
Derive insights to improve execution and realize superior performance. Understand pre-trade TCA without live AB tests.
Backtest execution algorithms with a realistic micro-structure and market slippage.
How does market simulation for banks work?
Common simulation modeling methodologies include historical replay and stochastic modeling. These techniques rely on historical data, which is an inaccurate way of measuring market impact due to no feedback, and are unlikely to take differences in market microstructure into account.
Agent-based modeling (ABM) is a state-of-the-art simulation methodology that drives critical decision-making in nuclear physics, medical research and applied artificial intelligence. What’s interesting about the ABM approach is that it focuses on capturing the market microstructure and the emergence of the price formation process.
These collective interactions are calibrated to generate market dynamics and stylized facts that match the specific price formation process for any selected security.
Our model, based on NASDAQ trading protocols, populates the market environment with different types of market participants, i.e. fundamental traders, momentum traders, market makers and noise traders. Calibrated simulations run up to 300x faster than real time.
Discover how you can accurately model market dynamics with a high-fidelity agent-based market simulator: 300x faster than real time.
Latest market execution resources
Tier 1 Bank