Quantitative Finance
Signaloid’s computing platform allows organizations such as hedge funds and investment banks to improve the accuracy and reduce the costs of their existing business-critical workloads that today employ Monte Carlo methods. Our technology allows organizations to use higher fidelity or more sophisticated models, enabling them to make better portfolio models, better risk analysis, better interest rate models, and ultimately to generate better returns.
Solutions
Choose between deployment models ranging from high-performance PCIe accelerator cards, to our on-premises virtualization and optimization layer, cloud-based compute infrastructure.
Example Performance Benchmarks
Achieve 2x–8x speedup with the same hardware resources, while achieving the same degree of convergence, for your options pricing and risk models that you currently implement using Monte Carlo methods. Give your existing optimized quant libraries an additional boost, with integration with your existing compilers and numerics libraries.
Technology Explainers
Compatibility with your existing CPU and GPU infrastructure, efficient digital representations of probability distributions, and efficient arithmetic on probability distributions. The technology explainers below provide more details on how Signaloid's technology works, in the context of Quantitative Finance applications, from the underlying mathematics to the engineering implementation and applications.
