An evolutionary theory of systemic risk and its mitigation for the global financial system

This thesis is the outcome of theory development research into an identified gap in knowledge about systemic risk of the global financial system. It takes a systems-theoretic approach, incorporating a simulation-constructivist orientation towards the meaning of theory and theory development, within a realist constructivism epistemology for knowledge generation about complex social phenomena. The specific purpose of which is to describe systemic risk of failure, and explain how it occurs in the global financial system, in order to diagnose and understand circumstances in which it arises, and offer insights into how that risk may be mitigated. An outline theory is developed, introducing a new operational definition of systemic risk of failure in which notions from evolutionary economics, finance and complexity science are combined with a general interpretation of entropy, to explain how catastrophic phenomena arise in that system. When a conceptual model incorporating the Icelandic financial system failure over the years 2003 – 2008 is constructed from this theory, and the results of simulation experiments using a verified computational representation of the model are validated with empirical data from that event, and corroborated by theoretical triangulation, a null-hypothesis about the theory is refuted. Furthermore, results show that interplay between a lack of diversity in system participation strategies and shared exposure to potential losses may be a key operational mechanism of catastrophic tensions arising in the supply and demand of financial services. These findings suggest new policy guidance for pre-emptive intervention calls for improved operational transparency from system participants, and prompt access to data about their operational behaviour, in order to prevent positive feedback inducing a failure of the system to operate within required parameters. The theory is then revised to reflect new insights exposed by simulation, and finally submitted as a new theory capable of unifying existing knowledge in this problem domain

Security in the Age of Systemic Risk: Strategies, Tactics and Options for Dealing with Femtorisks and Beyond

The world today is increasingly confronted with systemic threats and challenges, in which femtorisks - small-scale dangers that are inherent to system structures and function and which pose asymmetrically catastrophic risks - can build in consequence, spreading uncontrollably like epidemics in both natural and social systems in such diverse areas as ecology, epidemiology, finance, the Internet, terrorism, and international relations. They have been successfully modeled in ecology in the context of complex adaptive systems: systems made up of individual agents, whose interactions have macroscopic consequences that feed back to influence individual behavior. While acknowledging challenges, this paper argues for the value of applying to societal systems the approaches that natural scientists have developed in quantifying and modeling biological interactions and ecosystems

Nature inspired computational intelligence for financial contagion modelling

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.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 analyzing 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