Extreme market events and systemic collapses cause most of the popular attention to finance and financial markets. Extreme phenomena and the dynamics of con- nected/interacting systems have been the subject of financial modeling since early derivatives modeling, exposure risk modeling and portfolio construction. In the present work we discuss how traditional methods have for the most part failed to properly model the interconnected global financial and economic system. This led to systemic risk events and simplistic regulation which does not properly account for its implications. Analogously, we discuss how from as early as Mandelbrot’s works on financial prices and fat tails, academics, practitioners and regulators alike were warned of fat tails in financial modeling and in particular market making and derivatives pricing. The improper modeling or dismissal of these lies at the cen- tre of financial downturns ranging from LTCM’s collapse to the quant downturn of August 2007.
The solution I promote in this thesis is that of complexity and criticality. In line with this we propose two lines of work. The former analyses markets as complex networks and their structure through to practical takeaways including a proof of concept for portfolio construction. The latter instead focuses on extreme events in high frequency markets with results for both tail modeling and systemic events and practical insights from those. Recent events have shown how retail investors and their savings are now heavily involved in financial markets. We hope that our contribution of methods of practical use for proper risk modeling will encourage their adoption by practitioners and regulators with the outcome of a more stable and efficient financial system
