- author = "Monira Essa Aloud",
- title = "Modelling the High-Frequency {FX} Market: An Agent-Based Approach",
- school = "Department of Computing and Electronic Systems, University of Essex",
- year = "2013",
- address = "United Kingdom",
- month = apr,
- keywords = "genetic algorithms, genetic programming",
-
URL = "
http://fac.ksu.edu.sa/sites/default/files/MoniraAloud-Ph.D.Thesis.pdf",
- size = "183 pages",
-
abstract = "In this thesis, we use an agent-based modelling (ABM)
approach to model the trading activity in the Foreign
Exchange (FX) market which is the most liquid financial
market in the world. We first establish the statistical
properties (stylised facts) of the trading activity in
the FX market using a unique high-frequency dataset of
anonymised individual traders' historical transactions
on an account level, spanning 2.25 years. To the best
of our knowledge, this dataset is the biggest available
high-frequency dataset of individual FX market traders'
historical transactions. We then construct an
agentbased FX market (ABFXM) which features a number of
distinguishing elements including zero-intelligence
directional-change event (ZI-DCT0) trading agents and
asynchronous trading-time windows. The individual
agents are characterised by different levels of wealth,
trading time windows, different profit objectives and
risk appetites and initial activation conditions. Using
the identified stylized facts as a benchmark, we
evaluate the trading activity reproduced from the ABFXM
and we establish that this resembles to a satisfactory
level the trading activity of the real FX market.
In the course of this thesis, we study in depth the constructed ABFXM. We focus on performing a systematic exploration of the constituent elements of the ABFXM and their impact on the dynamics of the FX market behaviour. In particular, our study explores and identifies the essential elements under which the stylised facts of the FX market trading activity are exhibited in the ABFXM. Our study suggests that the key elements are the ZI-DCT0 agents, heterogeneity which has been embedded in our model in different ways, asynchronous trading time windows, initial activation conditions and the generation of limit orders. We also show that the dynamics of the market trading activity depend on the number of agents one considers.
We explore the emergence of the stylised facts in the trading activity when the ABFXM is populated with agents with three different strategies: a variation of the zero-intelligence with a constraint (ZI-CV) strategy; the ZI-DCT0 strategy; and a genetic programming-based (GP) strategy. Our results show that the ZI-DCT0 agents best reproduce and explain the stylised facts observed in the FX market transactions data. Our study suggests that some the observed stylised facts could be the result of introducing a threshold which triggers the agents to respond to fixed periodic patterns in the price time series.",
- notes = "Supervisor: Prof. Maria Fasli, Prof. Edward Tsang and Prof. Richard Olsen",
