Market Data Simulation

A simple electronic market is implemented where low intelligence agents engage in trading according to characteristics reported concerning typical patterns and statistics. We manage to recover distinctive patterns such as the U-shape of traded volume and gamma distributed order book while introducin...

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Main Author: Engman, Linus
Format: Others
Language:English
Published: Umeå universitet, Institutionen för datavetenskap 2014
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-90049
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spelling ndltd-UPSALLA1-oai-DiVA.org-umu-900492014-06-18T05:08:59ZMarket Data SimulationengEngman, LinusUmeå universitet, Institutionen för datavetenskap2014A simple electronic market is implemented where low intelligence agents engage in trading according to characteristics reported concerning typical patterns and statistics. We manage to recover distinctive patterns such as the U-shape of traded volume and gamma distributed order book while introducing a price driving process forcing the price towards its fundamental value. Two such processes are compared and shown to successfully produce market data explaining price paths almost indistinguishable from paths generated by stochastic processes such as the geometric Brownian motion. The introduction of the price driving processes makes it possible to force specific volatility, drift or similar features in addition to effortless generation of market data for correlated stocks. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-90049UMNAD ; 982application/pdfinfo:eu-repo/semantics/openAccess
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language English
format Others
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description A simple electronic market is implemented where low intelligence agents engage in trading according to characteristics reported concerning typical patterns and statistics. We manage to recover distinctive patterns such as the U-shape of traded volume and gamma distributed order book while introducing a price driving process forcing the price towards its fundamental value. Two such processes are compared and shown to successfully produce market data explaining price paths almost indistinguishable from paths generated by stochastic processes such as the geometric Brownian motion. The introduction of the price driving processes makes it possible to force specific volatility, drift or similar features in addition to effortless generation of market data for correlated stocks.
author Engman, Linus
spellingShingle Engman, Linus
Market Data Simulation
author_facet Engman, Linus
author_sort Engman, Linus
title Market Data Simulation
title_short Market Data Simulation
title_full Market Data Simulation
title_fullStr Market Data Simulation
title_full_unstemmed Market Data Simulation
title_sort market data simulation
publisher Umeå universitet, Institutionen för datavetenskap
publishDate 2014
url http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-90049
work_keys_str_mv AT engmanlinus marketdatasimulation
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