In 2007-08, the world experienced the greatest financial crisis since 1929, which turned – in the following years – in one of the deepest and most prolonged periods of economic stagnation of modern history. While there were multiple conditions that originated the so-called Great Financial Crisis, a general consensus emerged that financial derivatives played an important role in the outbreak of the crisis and in posing a credible threat that the entire global financial system could melt down. As a reaction, several countries in the world and international organizations agreed on a policy response to reformulate the global architecture for the regulation of the financial system, including the financial derivatives industry. Yet, the fundamental question of whether the contemporary system of derivatives regulation can effectively shield the financial system from sources of systemic risk is still undecided, for reasons that especially relate to the complexity of the networked structure of the financial derivatives industry. As a way to contribute to tackle this issue, this work aims to investigate whether an important component part of the present system of financial derivatives regulation – namely, Central Counterparts (CCPs) Clearing Houses – provide a more resilient financial system. The research question is addressed through a simulation approach based on an agent-based modeling of the financial derivatives industry. The results of the simulation show that the introduction of a CCP improves the resilience of the simulated financial derivatives industry, although it does not completely shield the financial system from disruptions that may especially depend from the degree of interconnectedness of financial operators and the magnitude of defaults. In sum, this work offers some methodological guidance for enriching the repertoire of tools at disposal of financial regulatory authorities in anticipating the consequences of interventions in the financial industry.
The regulation of financial derivates: an agent-based model approach
KRACHKOVSKAYA, INNA
2015-05-28
Abstract
In 2007-08, the world experienced the greatest financial crisis since 1929, which turned – in the following years – in one of the deepest and most prolonged periods of economic stagnation of modern history. While there were multiple conditions that originated the so-called Great Financial Crisis, a general consensus emerged that financial derivatives played an important role in the outbreak of the crisis and in posing a credible threat that the entire global financial system could melt down. As a reaction, several countries in the world and international organizations agreed on a policy response to reformulate the global architecture for the regulation of the financial system, including the financial derivatives industry. Yet, the fundamental question of whether the contemporary system of derivatives regulation can effectively shield the financial system from sources of systemic risk is still undecided, for reasons that especially relate to the complexity of the networked structure of the financial derivatives industry. As a way to contribute to tackle this issue, this work aims to investigate whether an important component part of the present system of financial derivatives regulation – namely, Central Counterparts (CCPs) Clearing Houses – provide a more resilient financial system. The research question is addressed through a simulation approach based on an agent-based modeling of the financial derivatives industry. The results of the simulation show that the introduction of a CCP improves the resilience of the simulated financial derivatives industry, although it does not completely shield the financial system from disruptions that may especially depend from the degree of interconnectedness of financial operators and the magnitude of defaults. In sum, this work offers some methodological guidance for enriching the repertoire of tools at disposal of financial regulatory authorities in anticipating the consequences of interventions in the financial industry.File | Dimensione | Formato | |
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