Nature inspired computational intelligence for financial contagion modelling

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Fang Liu",
  title =        "Nature inspired computational intelligence for
                 financial contagion modelling",
  school =       "College of Business, Arts and Social Sciences, Brunel
  year =         "2014",
  address =      "UK",
  month =        "22 " # feb,
  keywords =     "genetic algorithms, genetic programming, FGP, PSO,
                 Particle swarm optimization, Independence, Copula, Game
  URL =          "",
  URL =          "",
  size =         "190 pages",
  abstract =     "Financial contagion refers to a scenario in which
                 small shocks, which initially affect only a few
                 financial institutions or a particular region of the
                 economy, spread to the rest of the financial sector and
                 other countries whose economies were previously
                 healthy. This resembles the “transmission” of a
                 medical disease. Financial contagion happens both at
                 domestic level and international level. At domestic
                 level, usually the failure of a domestic bank or
                 financial intermediary triggers transmission by
                 defaulting on inter-bank liabilities, selling assets in
                 a fire sale, and undermining confidence in similar
                 banks. An example of this phenomenon is the failure of
                 Lehman Brothers and the subsequent turmoil in the US
                 financial markets. International financial contagion
                 happens in both advanced economies and developing
                 economies, and is the transmission of financial crises
                 across financial markets. Within the current globalise
                 financial system, with large volumes of cash flow and
                 cross-regional operations of large banks and hedge
                 funds, financial contagion usually happens
                 simultaneously among both domestic institutions and
                 across countries. There is no conclusive definition of
                 financial contagion, most research papers study
                 contagion by analysing the change in the
                 variance-covariance matrix during the period of market
                 turmoil. King and Wadhwani (1990) first test the
                 correlations between the US, UK and Japan, during the
                 US stock market crash of 1987. Boyer (1997) finds
                 significant increases in correlation during financial
                 crises, and reinforces a definition of financial
                 contagion as a correlation changing during the crash
                 period. Forbes and Rigobon (2002) give a definition of
                 financial contagion. In their work, the term
                 interdependence is used as the alternative to
                 contagion. They claim that for the period they study,
                 there is no contagion but only interdependence.
                 Interdependence leads to common price movements during
                 periods both of stability and turmoil. In the past two
                 decades, many studies (e.g. Kaminsky et at., 1998;
                 Kaminsky 1999) have developed early warning systems
                 focused on the origins of financial crises rather than
                 on financial contagion. Further authors (e.g. Forbes
                 and Rigobon, 2002; Caporale et al, 2005), on the other
                 hand, have focused on studying contagion or
                 interdependence. In this thesis, an overall mechanism
                 is proposed that simulates characteristics of
                 propagating crisis through contagion. Within that
                 scope, a new co-evolutionary market model is developed,
                 where some of the technical traders change their
                 behaviour during crisis to transform into herd traders
                 making their decisions based on market sentiment rather
                 than underlying strategies or factors. The thesis
                 focuses on the transformation of market interdependence
                 into contagion and on the contagion effects. The author
                 first build a multi-national platform to allow
                 different type of players to trade implementing their
                 own rules and considering information from the domestic
                 and a foreign market. Traders strategies and the
                 performance of the simulated domestic market are
                 trained using historical prices on both markets, and
                 optimizing artificial market's parameters through
                 immune - particle swarm optimization techniques
                 (I-PSO). The author also introduces a mechanism
                 contributing to the transformation of technical into
                 herd traders. A generalized auto-regressive conditional
                 heteroscedasticity - copula (GARCH-copula) is further
                 applied to calculate the tail dependence between the
                 affected market and the origin of the crisis, and that
                 parameter is used in the fitness function for selecting
                 the best solutions within the evolving population of
                 possible model parameters, and therefore in the
                 optimization criteria for contagion simulation. The
                 overall model is also applied in predictive mode, where
                 the author optimize in the pre-crisis period using data
                 from the domestic market and the crisis-origin foreign
                 market, and predict in the crisis period using data
                 from the foreign market and predicting the affected
                 domestic market.",
  notes =        "Mention of GP

                 Supervisor Antoaneta Serguieva and P.Date",

Genetic Programming entries for Fang Liu