Who we are

TFG Financial Systems provides an institutional quality platform for cross-asset portfolio and real time risk management to hedge funds, asset managers, and banks.

The software is cloud based and provided as a service, enabling quick and efficient installation. From initial contact through to entering your first trade and beyond, TFG gives you unlimited access to its team of specialists easing the technology burden and allowing you to focus on your business.

Our flagship product covers every step of the investment process – from market monitoring, trade capture and portfolio valuation, through to monitoring of portfolio risk and performance, all handled within a single platform. We have been delivering robust technology solutions to complex risk management problems for more than 10 years, with clients in Europe, North America and Asia.

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Latest news

  • Barak Fund Management chooses TFG Complete for real time risk management support

    Barak Fund Management, an Africa-focused alternative fund management company, has chosen TFG Financial Systems to provide it with TFG Complete, TFG’s fully integrated middle office and risk management system. TFG will be supporting two new Barak funds, investing in the commodities and forex markets respectively. Barak is a specialist in commodity-focused investment opportunities and trade […]
  • Hedge funds facing increased investor demand for STP efficiencies

    TFG Financial Systems reports further take up of its TFG Complete enhanced STP service on the back of more stringent investor requirements. TFG Financial Systems, a leading provider of real time risk and portfolio management systems, has said it is seeing increased adoption of the straight through processing (STP) workflow module of its core portfolio […]

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White Papers

Option Valuation using Finite Differences

Martin Toyer, TFG Systems,

TFG has built a method to value options with a non-standard pay-out function and Knock-Out barriers. As this calculation is integrated into a real-time system, performance and stability are critical. This has been achieved by using implicit finite differences where more detailed grids are used when the estimate of the error exceeds the required tolerance.

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