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Accuracy and High Performance

Backtest trading models; from low to high frequency strategies.

By using the same source code for paper trading and production, you will reduce the elapsed time for implementation project as well as the associated operational risk.

Run stress testing to determine the stability and the safe usage limits of the trading algorithms.

Export comprehensive post trade data sets for easy analysis using ubiquitous applications.

Backtesting a trading model is quite straightforward when you use the Systemathics tools and approach. The backtesting process follows three steps: Backtesting : Data Mining, Simulation and Post-trade Analysis

  • The data mining step of the Backtesting normalizes data and builds the storyboard.
  • The simulation step of the Backtesting runs the strategy : processing data, generating signals and handling orders and executions.
  • The analysis step of the Backtesting generates post-trade analysis and reports.

Code Invariance
Smart Simulation
Data Streaming
    • Use the same C# source code for back-test, paper trading and production
    • Comprehensive SDK with samples and tutorials
    • Microsoft Visual Studio integration

    • High performance execution simulator for both low and high frequency strategies
    • Production data flow including pre-trade security checks
    • Smart order execution to take advantage of market liquidity

    • Generate Storyboards for efficient binary streaming
    • Leverage inhouse historical data using convenient APIs
    • Native support for Data Mining Engine

    • Azure and HPC drivers for extreme scenarios
    • Scripting capabilities for batch and overnight simulations
    • Task scheduler to run multiple scenarios in parallel

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