MathFinance has started a business relationship with Volmaster FX
Stochastic-local volatility models have been one of our primary activities over the last years. It became clear that the market consensus modeling approach for first generation exotic options would be SLV middle of the last decade, so many years ago. So what's the problem? There are thousands of talented quants out there in the industry, so why doesn't everybody have an SLV model? First of all, even within the class of SLV models many choices have to be made and their performance has to be tested. Do we want a Heston model for the stochastic volatility part or rather another diffusion? Should we model the local volatility function parametric or non-parametric? Each choice triggers a complex calibration problem. Few SLV models admit a closed-form solution for vanilla options: Murex came up with a proprietary closed form approximation for a Heston model with a parabolic parametrization of the local volatility. This helped speeding up the calibration and they were first to offer a workable SLV model within their risk management system. We performed an intensive validation of what Murex calls the Tremor model in 2010 and 2011. Since calibration is time consuming, the market did in fact have to wait for the hardware to be ready to cope with the requirements of speed. And having a prototype of an SLV model ready is only a first step; its integration into a front office tool or a risk management system is yet another exercise.
Currently, the situation is that the top tier banks will have their in-house SLV model(s). Some others have a prototype and might be close to putting it in production, but the majority are still aiming to build one or are looking for other access methods. Smaller banks and the buy-side have very limited access to such state-of-the-art models. I will give an overview on the models next week in London, see below.
The market consensus price for a double-no-touch can be seen in the graph that shows TV (theoretical value) on the x-axis and the difference to TV in various models on the y-axis. It clearly points out that neither a pure stochastic volatility model (such as Heston) nor a pure local volatility model generate prices inside the bid-offer spread of the double-no-touch.
There are very limited solutions in the market, but we found Volmaster a while ago and had a closer look. MathFinance has always been very passionate about FX derivatives and we are now pleased to announce that we started a business relationship with Volmaster FX.
Uwe Wystup, Managing Director, MathFinance AG, says:
"This new on-line pricing tool for FX derivatives, with its cutting-edge technology and its native pricing on advanced models (stochastic-local volatility, jumps) represents a new generation of financial software. Fast, precise, transparent, easy to integrate into existing infrastructures, expandable and future-proof. We are very pleased to have Volmaster as our new business partner and to be a part of this new and exciting tool."
Stefano Silvano, Volmaster CEO, comments:
"We are delighted to cooperate with MathFinance. We believe that MathFinance, as a leading financial boutique, can significantly contribute to new exciting developments of our acclaimed Volmaster FX pricing tool. Since Volmaster FX has been conceived and developed following a scientific approach, we are particularly excited about the depth of academically-backed know-how and skillsets MathFinance can offer."
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