aklamun / optimal_intervention

Algorithms for optimal intervention in financial networks

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Optimal_Intervention

Code from paper Optimal Intervention in Economic Networks using Influence Maximization Methods

Presented at NetSci Conference 2020, talk available here

Code files are described as follows:

  • GJ_cascade_dense.py = cascade model and intervention approximation algorithms
  • wiot_network.py = parses WIOD data and constructs graph objects
  • simulate_shocks.py = functionality to set up and run shock simulations
  • interpret_data.py = functionality to calculate tail value at risk for simulations
  • run_simulation.py = run simulations and generate figures

World Input Output Database (WIOD) data is available here


This material is based on work funded by the NSF and a Bloomberg Fellowship

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Algorithms for optimal intervention in financial networks


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