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This paper discusses the implementation of one-factor and three-factor PDE models on GPUs. Both explicit and implicit time-marching methods are considered, with the latter requiring the solution of multiple tridiagonal systems of equations.

Because of ...

Calibration methods are the heart of modeling any financial process. While for the Heston model (semi) closed-form solutions exist for calibrating to simple products, their evaluation involves complex functions and infinite integrals. So far these ...

Quantitative financial analysis requires repeated computations of the same functions with the same arguments when prototyping trading strategies; many of these functions involve resource intensive operations on large matrices. Reducing the number of ...

Financial markets change precipitously and on-demand pricing and risk models must be constantly recalibrated to reduce risk. However, certain classes of models are computationally intensive to robustly calibrate to intraday prices-stochastic volatility ...

Energy consumption and total cost of ownership are daunting challenges for Datacenters, because they scale disproportionately with performance. Datacenters running financial analytics may incur extremely high operational costs in order to meet ...

Most popular analysis tools on time series require the data to be taken at uniform time intervals. However, the real-world time series, such as those from financial markets, are typically taken at irregular time intervals. It is a common practice to ...

In this paper, we discuss the problem of pricing one exotic option, the strong path dependent Asian option using the Black--Scholes model and compare how the pricing algorithm can map into different many-core architectures and achieve equally impressive ...

STAC-A2^™ is compute and memory intensive industry benchmark in the field of market risk analysis. The benchmark specifications were created by the Securities Technology Analysis Center (aka STAC®) and are based on inputs collected from the leading ...