UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Large-scale simulations of synthetic markets

Gerardo-Giorda, L; Germano, G; Scalas, E; (2015) Large-scale simulations of synthetic markets. Communications in Applied and Industrial Mathematics , 6 (2) pp. 1-14. 10.1685/journal.caim.535. Green open access

[thumbnail of CommunApplIndMath_6_535_2014.pdf]
Preview
Text
CommunApplIndMath_6_535_2014.pdf

Download (1MB) | Preview

Abstract

High-frequency trading has been experiencing an increase of interest both for practical purposes within financial institutions and within academic research; recently, the UK Government Office for Science reviewed the state of the art and gave an outlook analysis. Therefore, models for tick-by-tick financial time series are becoming more and more important. Together with high-frequency trading comes the need for fast simulations of full synthetic markets for several purposes including scenario analyses for risk evaluation. These simulations are very suitable to be run on massively parallel architectures. Aside more traditional large-scale parallel computers, high-end personal computers equipped with several multi-core CPUs and general-purpose GPU programming are gaining importance as cheap and easily available alternatives. A further option are FPGAs. In all cases, development can be done in a unified framework with standard C or C++ code and calls to appropriate libraries like MPI (for CPUs) or CUDA for (GPGPUs). Here we present such a prototype simulation of a synthetic regulated equity market. The basic ingredients to build a synthetic share are two sequences of random variables, one for the inter-trade durations and one for the tick-by-tick logarithmic returns. Our extensive simulations are based on several distributional choices for the above random variables, including Mittag-Leffler distributed inter-trade durations and alpha-stable tick-by-tick logarithmic returns.

Type: Article
Title: Large-scale simulations of synthetic markets
Open access status: An open access version is available from UCL Discovery
DOI: 10.1685/journal.caim.535
Publisher version: http://dx.doi.org/10.1685/journal.caim.535
Language: English
Additional information: This work is licensed under a Creative Commons Attribution NonCommercial NoDerivs 3.0 License.
Keywords: synthetic markets, large scale simulation, heteroskedasticity
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1473563
Downloads since deposit
80Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item