Big Data and Graph Theoretic Models: Simulating the Impact of Collateralization on a Financial System
8 Pages Posted: 1 Jun 2017
Date Written: May 29, 2017
In this paper we represent a financial system using a weighted directed graph model. We simulate and analyze the impact of financial regulations regarding the collateralization of derivative trades on systemic risk, employing a novel open source risk engine. The analysis finds that introducing collateralization does reduce the costs of resolving a financial system in crisis. It does not, however, change the distribution of risk in the system. The implications of the analysis highlight the importance of scenario based testing using hands on metrics to quantify the notion of system risk.
Keywords: Big Data, Graph Theoretic Models, Stochastic Linear Gauss-Markov Model, Monte Carlo Simulation, Financial Risk Analytics, Collateralizations, Variation Margin, Initial Margin, Open Source Risk Engine
JEL Classification: G01, G18, G28, G32, G38, C12, C15
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