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Big Data and Graph Theoretic Models: Simulating the Impact of Collateralization on a Financial System

Published:31 July 2017Publication History

ABSTRACT

In this paper, we simulate and analyze the impact of financial regulations concerning the collateralization of derivative trades on systemic risk. We represent a financial system using a weighted directed graph model. We enhance a novel open source risk engine to automatically classify a financial regulation for its impact on systemic risk. 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 analysis also highlights the importance of scenario based testing using hands on metrics to quantify the notion of system risk.

References

  1. Adrian T, Brunnermeier M K. "CoVaR". The American Economic Review, 2016, 106(7): 1705--1741 Google ScholarGoogle ScholarCross RefCross Ref
  2. Andersen, L., M. Pykhtin, and A. Sokol, "Credit Exposure in the Presence of Initial Margin," SSRN pre-print, 2016.Google ScholarGoogle Scholar
  3. Andersen, Leif. Pykhtin, Michael. Sokol, Alexander. "Does initial marign eliminate counterparty risk?", risk.net, 05/2017Google ScholarGoogle Scholar
  4. Anfuso, F., D. Aziz, P. Giltinan, and K. Loukopoulos, "A Sound Modelling and Backtesting Framework for Forecasting Initial Margin Requirements," SSRN pre-print, 2016.Google ScholarGoogle Scholar
  5. Bales, M., and S. Johnson, "Graph theoretic modeling of large-scale semantic networks," Journal of Biomedical Informatics, Volume 39, Issue 4, August 2006, Pages 451--464. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Billio, M., M. Getmansky, A. W. Lo, and L. Pelizzon, 2010, "Econometric measures of systemic risk in the finance and insurance sectors," NBER Working Paper 16223, NBERGoogle ScholarGoogle Scholar
  7. Bisias, Dimitrios. Flood, Mark. Lo, Andrew W.. Valavanis, Stavros. "A Survey of Systemic Risk Analytics", Office of Financial Research, Working Paper #0001, January 5, 2012,Google ScholarGoogle Scholar
  8. Cont, R., Moussa, A., & Santos, E. (2013). "Network Structure and Systemic Risk in Banking Systems". In J. Fouque & J. Langsam (Eds.), Handbook on Systemic Risk (pp. 327--368). Cambridge: Cambridge University Press. doi:10.1017/CBO9781139151184.018 Google ScholarGoogle ScholarCross RefCross Ref
  9. Caspers, P., Giltinan, P., Lichters, R., Nowaczyk, N. "Forecasting Initial Margin Requirements -- A Model Evaluation", SSRN pre-print, 2017.Google ScholarGoogle Scholar
  10. ISDA, "ISDA SIMM (TM) Methodology", Version R1.0, September 2016.Google ScholarGoogle Scholar
  11. Lichters, R. Stamm, R. Gallagher, D. Modern Derivatives Pricing and Credit Exposure Analysis: Theory and Practice of CVA and XVA Pricing, Exposure Simulation and Backtesting (Applied Quantitative Finance), Palgrave Macmillan, 2015.Google ScholarGoogle Scholar
  12. "Open Source Risk Engine", www.opensourcerisk.org. First release in October 2016Google ScholarGoogle Scholar
  1. Big Data and Graph Theoretic Models: Simulating the Impact of Collateralization on a Financial System

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