An Empirical Investigation of Price Impact: An Agent-based Modelling Approach

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@PhdThesis{wei:thesis,
  author =       "Wei Cui",
  title =        "An Empirical Investigation of Price Impact: An
                 Agent-based Modelling Approach",
  school =       "Michael Smurfit School of Business University College
                 Dublin",
  year =         "2012",
  address =      "Ireland",
  month =        nov,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://ncra.ucd.ie/papers/wei_thesis.pdf",
  size =         "268 pages",
  abstract =     "Understanding price impact is a fundamental task in
                 finance. Many execution algorithms, used to execute a
                 large order by dividing and spreading it over time, are
                 based on price effects and in particular on the way how
                 volume affects prices. Moreover, the analysis of price
                 impact is helpful for understanding how financial
                 markets function as price impact is one of the
                 mechanisms determining price formation.

                 The thesis is motivated by the recent emergence of
                 algorithmic trading which requires a good understanding
                 of price impact. This thesis addresses three questions
                 concerning price impact in order to gain a better
                 understanding on the intraday behaviour of price
                 impact, and the factors affecting price impact.

                 The first study examines the intraday behaviours of
                 price impact and market liquidity. The data is drawn
                 from the NYSE-Euronext TAQ database and the LSE ROB
                 database. Six stocks from the US markets and six stocks
                 from the UK markets are analysed. The intraday patterns
                 on price volatility, bid-ask spread, trading volume and
                 market depth are documented and generally confirm
                 findings in prior studies on intraday phenomena. In
                 particular, a reverse S-shaped intraday pattern on
                 price impact is found for both US and UK stocks for the
                 first time.

                 The second study investigates whether agent
                 intelligence plays an important role in determining the
                 magnitude of price impact. This chapter constructs an
                 artificial stock market composed of zero-intelligence
                 agents, and calibrates it using the LSE ROB data. The
                 result shows that the price impact in the artificial
                 market is generally larger than that in the real
                 market. This is consistent with the hypothesis that
                 agent intelligence plays an important role in
                 determining the magnitude of price impact. It supports
                 the selective liquidity argument in Farmer et al.
                 (2004) & Hopman (2007).

                 The third study addresses whether order choice affects
                 the price impact of trading a large order. A typical
                 approach in trading a large order is to devise a
                 strategy which divides it into numerous pieces and
                 spreads it over time (usually one trading day). In this
                 study, several execution strategies with various order
                 types, and a number of simple strategies with one order
                 type as benchmarks are constructed and evaluated by
                 their effects on prices. Novelly, these strategies are
                 evolved and evaluated in simulated artificial markets.
                 The results show that the combined strategies
                 outperform the simple strategies significantly,
                 suggesting that order choice plays an important role in
                 determining the price impact of trading large
                 orders.

                 The results in this thesis suggest that
                 time-of-the-day, agent intelligence and order choice
                 are important factors affecting price impact, and need
                 to be considered in the theoretical microstructure
                 models and in the design of trading strategies.",
  notes =        "Research Supervisor: Prof. Anthony Brabazon",
}

Genetic Programming entries for Wei Cui

Citations