Scalable system with accelerators for financial option prices estimation Online publication date: Fri, 06-Jan-2017
by D. Dimitrov; E. Atanassov
International Journal of Data Science (IJDS), Vol. 1, No. 4, 2016
Abstract: In this paper we describe a production-ready enterprise service bus (ESB) system for estimation of option prices using stochastic volatility models. We present the motivation for our research, the main building blocks for our system and discuss our approach for calibration of the Heston model. The Heston model is used as a basis for modelling the evolution of asset prices. The Zato framework is used as an integration layer, while the main computations are distributed to HPC resources (GPUs and Intel Xeon Phi cards). The system can use various data sources and scales from both infrastructure and software point of view. The main advantage of the system is that by incorporating general-purpose computing on graphics processing units (GPGPU) and Intel Xeon Phi nodes it allows for the use of more accurate models that are otherwise unfeasible. This system can be useful for distributed processing of a large volume of option pricing tasks.
Online publication date: Fri, 06-Jan-2017
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Science (IJDS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com