An Optimization View of Financial Systemic Risk Modeling: Network Effect and Market Liquidity Effect

An Optimization View of Financial Systemic Risk Modeling: Network Effect and Market Liquidity Effect

0.00 Avg rating0 Votes
Article ID: iaor20164534
Volume: 64
Issue: 5
Start Page Number: 1089
End Page Number: 1108
Publication Date: Oct 2016
Journal: Operations Research
Authors: , ,
Keywords: optimization, investment, risk, simulation, networks, behaviour
Abstract:

Financial institutions are interconnected directly by holding debt claims against each other (the network channel), and they are also bound by the market when selling assets to raise cash in distressful circumstances (the liquidity channel). The goal of our study is to investigate how these two channels of risk interact to propagate individual defaults to a systemwide catastrophe. We formulate a constrained optimization problem that incorporates both channels of risk, and exploit the problem structure to generate the solution (to the clearing payment vector) via a partition algorithm. Through sensitivity analysis, we are able to identify two key contributors to financial systemic risk, the network multiplier and the liquidity amplifier, and to discern the qualitative difference between the two, confirming that the market liquidity effect has a great potential to cause systemwide contagion. We illustrate the network and market liquidity effects–in particular, the significance of the latter–in the formation of systemic risk with data from the European banking system. Our results contribute to a better understanding of the effectiveness of certain policy interventions. In addition, our algorithm can be used to pin down the changes of the net worth (marked to market) of each bank in the system as the spillover effect spreads, so as to estimate the extent of contagion, and to provide a metric of financial resilience as well. Our framework can also be easily extended to incorporate the effect of bankruptcy costs.

Reviews

Required fields are marked *. Your email address will not be published.