Simulation Engine

Our proprietary engine is designed to simulate revenue scenarios driven by the broker’s choice of different factors applied to filter trades for running a B Book. The outcome of the scenarios will be highly dependent on the broker’s tolerance for risk.

In addition to accounting for rebates, the simulation may also assume different notional volume levels in order to examine how both the notional volumes & factor filtering impact revenues.

Finally, through the Revenue Per Million (RPM) calculation, we capture a mix of market conditions and the type of flow the broker faced throughout the last 3 years. We simulate different RPM levels over different timeframes in order to project best-case and worst-case revenues scenarios. The simulation enables the broker to strengthen its cash planning abilities.

Volumes and their associated cost are a critical part of the analysis. FX brokers running a B Book should aim to have enough business to be profitable on a consistent basis. To do so, brokers seek a minimum level of volumes to allow for the implementation of a hybrid model to generate enough risk-free business (net spreads and commissions from A/B books) to counterbalance B-book volatility from warehousing activities (market movements on B Book positions).  

Many small brokers are forced to run a high-risk hybrid model to be able to generate enough revenues to cover their costs. Determining the optimal allocation between high-risk and risk-free business (A & B Books allocation) is complicated without the proper flow classification and a clear understanding of revenue drivers.

Our engine is built using MATLAB.  

Key Benefits

Ability to back-test different Hybrid models before implementing

Ability to measure the risk-adjusted return of the Hybrid model before implementing

Identify the company’s breakeven volume level that ideally produces 100% positive trading days and months

Solid model optimization based on simulation findings

Determine required funding to finance the worst possible streak for the Hybrid model before implementing

Ability to quantify the effect of volume on the daily and monthly stability of revenue and calibrate the Hybrid model to target desired level of volatility