Back-test Your Hybrid Model

Determine the optimal hybrid model to secure the best risk-adjusted performance
Foresee challenges & opportunities

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. 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 capital forecasting abilities.


The C-Simulation engine was built specifically to equip you with the information you need to wisely allocate your A/B Books. This technology will allow you to establish a stronger business, whether you’re implementing a high-risk, or low-risk hybrid.

Contact us

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. The engine is built using big data technology and tick historical prices.


Revolutionary real-time portfolio stress-test engine for price gap scenario using preset price percent move for either a selection of instruments or all instruments. It forecasts client’s negative balances, company P/L, company net positions, triggered orders (take profit, stop loss, buy limit, buy stop, sell limit, sell stop, and margin stop out) per instrument and for the portfolio. The forecast is performed on two cases for the same price gap percentage move (in favor and against the company pre-gap net position for each instrument)


Test volume levels to implement an optimized hybrid model

Secure profitable Net Spreads & Commission from A/B Books allocations

Measure the risk-adjusted return of the hybrid model before implementing

Counterbalance B-Book volatility from warehousing activities; market movements on B positions

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

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