Modelling the High-Frequency FX Market: An Agent-Based Approach

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@PhdThesis{MoniraAloud-Ph.D.Thesis,
  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",
}

Genetic Programming entries for Monira Aloud

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