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Digital Library of the
European Council for Modelling and Simulation |
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Title: |
Preventing Collapse Of Financial
Networks Through Systemic Risk Taxes |
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Authors: |
Stefan Thurner
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Published in:
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(2014).ECMS 2014 Proceedings edited
by: Flaminio Squazzoni,
Fabio Baronio, Claudia Archetti,
Marco Castellani European Council for
Modeling and Simulation. doi:10.7148/2014 ISBN:
978-0-9564944-8-1 28th
European Conference on Modelling and Simulation, Brescia,
Italy, May 27th – 30th,
2014 |
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Citation
format: |
Stefan Thurner
(2014). Preventing Collapse Of Financial Networks Through Systemic Risk Taxes
- Answers From Agent Based Models, ECMS 2014 Proceedings
edited by: Flaminio Squazzoni,
Fabio Baronio, Claudia Archetti,
Marco Castellani European Council for Modeling and Simulation. doi:10.7148/2014-0005 |
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DOI: |
http://dx.doi.org/10.7148/2014-0005 |
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Abstract: |
Financial
markets are exposed to systemic risk (SR), the risk that the system ceases to
function and collapses. Since recently, it is possible to quantify SR in terms
of underlying financial (multiplex) networks where nodes represent financial
institutions, and links capture financial contracts such as loans, credits,
or derivatives. We show that it is possible to quantify in real data the SR
of individual transactions in a financial network. We propose a tax on
individual transactions that is proportional to their contribution to the
overall SR. If a transaction does not increase SR, it is tax
free. We demonstrate
with an agent based model (CRISIS macro-financial model) that the proposed
Systemic Risk Tax (SRT) leads to a selforganized re-structuring
of financial networks that are practically free of SR. ABM
predictions agree remarkably well with the empirical data and can be used to
understand the relation of credit risk and SR. |
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