Login / Signup

Uncovering the network structure of non-centrally cleared derivative markets: evidence from large regulatory data.

Sebastiano Michele Zema
Published in: Empirical economics (2023)
The network structure of non-centrally cleared derivative markets, uncovered via the European Market Infrastructure Regulation, is investigated by reconstructing initial and variation margin networks to analyze channels of potential losses and liquidity dynamics. Despite the absence of central clearing, the derivative network is found to be ultra-small and a maximization-based filtering tool is proposed to identify channels in the network characterized by the highest exposures. I find these exposures to be mainly toward institutions outside the euro area, emphasizing the need for cooperation across different jurisdictions. Anomalous behavior in terms of diverging first and second moments of the degree and strength distributions are detected, signaling the presence of large exposures generating extreme liquidity outflows. A reference table of parameters' estimates based on real data is provided for different network sizes, with no break of confidentiality, making it possible to simulate in a realistic way the liquidity dynamic in global derivative markets even when access to supervisory data is not granted.
Keyphrases
  • electronic health record
  • air pollution
  • big data
  • risk assessment
  • network analysis
  • water soluble
  • health insurance
  • deep learning
  • mass spectrometry
  • data analysis