(NEW YORK)–A team collaborating out of Columbia University is studying the use of data science techniques to understand and reduce systemic counter-party risk in the ever growing world of complex derivative ‘quant’ trading.
The financial crisis of 2008, and even more recently the market meltdown from the collapse of complex derivatives in the CBOE Volatility Index (VIX), shows the importance for larger financial firms to use new tools such as A.I. to find out risk before it happens.
Titled “A Data Science Approach to Predict the Impact of Collateralization on Systemic Risk“, the research project simulates and analyzes the impact of financial regulations concerning the collateralization of derivative trades on systemic risk, which has been vigorously discussed since the 2008 financial crisis.
In their project they adapt a simulation technology combining advances in graph theory to randomly generate entire financial systems sampled from realistic distributions with a novel open source risk engine to compute risks in financial systems under different regulations. This allows them to consistently evaluate, predict and optimize the impact of financial regulations on all levels – from a single trade to systemic risk – before it is implemented.
The project is in collaboration with Columbia University Fintech Lab, and is headed up by Prof. Sharyn O’Halloran, Ph.D. from Columbia School of International & Public Affairs, Nikolai Nowaczyk, PhD and Donal A. Gallagher, PhD, both from Quaternion Risk Management. www.quaternion.com
Nikolai Nowaczyk, one of the lead authors on the project commented, “Combining data science technologies with an open source risk engine enabled us to bridge the gap between macro- and micro-economics, which often makes it difficult to quantitatively study the impact of financial regulations. The Fintech lab allowed us to bridge the gap between academia and the business.”
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About Fintech Lab Columbia University
The FinTech Lab will explore collaborative research applications of open source software tools that focus on systemic counterparty risk within the global financial system. This open source initiative will increase the industry’s financial literacy by broadening public access to quantitative financial models, improve model performance through intense public scrutiny, and reduce systemic risk by giving smaller, potentially less sophisticated institutions and governments the proper tools to calculate and comprehend their risk exposures. http://fintech.datascience.columbia.edu/
Quaternion Risk Management
Phone: +44 207712 1645
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Columbia School of International & Public Affairs
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