We propose a novel framework to model financial markets as complex systems and develop a control methodology for systemic risk as an alternative to the current regulatory and policy-making approaches.
- Machine Learning
- Risk and Decision Analysis
- systemic risk
The 2007–8 financial crisis and its aftermath illustrated the fundamental shortcomings of the existing regulatory and policy-making approaches to recognize and mitigate systemic risk in financial markets and thereby maintain the stability of the economy. Ten years later, we still have no comprehensive framework to monitor/mitigate systemic risk and lack reliable and efficient methods to predict and avoid financial crises. Mainstream research and practice in this field focus on extending existing theories and regulatory approaches to cover the newly recognized phenomenon of systemic risk. Those theories and approaches, however, were developed for the purpose of regulating a traditionally structured banking industry in which the principal business consisted of aggregating small deposits into secured collateral consumer loans. The systemic risk models in the literature do not address modern financial systems, which are complex interconnected sets of institutions with numerous interacting channels for activities that even the exposed banks themselves, let alone regulators and policymakers, may not be able to observe.
We propose a novel mathematical framework to model financial markets as complex systems of economic interactions and contractual and legal obligations aiming to understand, measure and mitigate systemic risk exposure of economy from the perspective of the policymakers and regulators. The proposed mechanism aims to exploit the systemic structure of contractual dependencies of the financial institutions in a competitive market where banks maximize their individual share of the financial market/profit. To do so, we need to develop an economy of such financial systems capturing the market dynamics and consistent with legal rules and regulatory frameworks.
The resulting model should be a reasonable basis to define a measure of systemic risk associated with each financial institution. Ideally, the model will also be a framework for developing alternative regulatory methods to mitigate aggregate systemic risk exposure of the economy, subject to minimum regulatory and economic intervention and an economy of fixed size. We aim to show that, our methodology is a plausible and efficient framework to design better regulatory alternatives than the existing ones.
The main outcome and contribution of this research project is to develop a comprehensive approach for modeling and measuring systemic risk in financial markets through complex systems modeling and bringing together the perspectives of the economics and law disciplines in a coherent framework which is missing from the literature of systemic risk.
More specifically, the outcomes we will try to achieve are:
- A mathematical modeling framework for financial markets and systemic risk that overcomes the theoretical limitations of the existing literature and accordingly provides a rigorous ground for the methodologic extensions, and practical implementations of the resulting methods.
- Computationally tractability measures of a) Systemic risk contribution of individual banks to overall system and b) Aggregate systemic risk exposure of the economy and financial system
- Regulatory and policy-making framework, proposed for systemic risk management that is consistent with modern banking business models and legal rules and is practically implementable.
This project will fund a Ph.D. student with a research background in economics, mathematics, law and systems engineering. He has the experience of conducting different intradisciplinary research projects and worked with the faculties in different departments. If initial results are promising, this may lead in recruiting more undergrad and graduate students based on follow-on proposals to foundation and federal funding programs.
The proposed project is highly interdisciplinary in nature and therefore unlikely to receive funding from traditional sources without strong initial results. The 3 Cavaliers program provides a unique opportunity to fund a Ph.D. student that has sufficient experience in bringing together the perspectives of the faculties from several different disciplines to address a problem of significant societal concern.