Applying CVaR for decentralized risk management of financial companies

John M. Mulvey, Hafize G. Erkan

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Over the past decade, financial companies have merged diverse areas including investment banking, insurance, retail banking, and trading operations. Despite this diversity, many global financial firms suffered severe losses during the recent recession. To reduce enterprise risks and increase profits, we apply a decentralized risk management strategy based on a stochastic optimization model. We extend the decentralized approach with the CVaR risk-metric, showing the advantages of CVaR over traditional risk measures such as value-at-risk. An example taken from the earthquake insurance area illustrates the concepts.

Original languageEnglish (US)
Pages (from-to)627-644
Number of pages18
JournalJournal of Banking and Finance
Issue number2
StatePublished - Feb 2006

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics and Econometrics


  • Conditional value-at-risk
  • Decentralized optimization
  • Risk management
  • Risk measures
  • Utility optimization


Dive into the research topics of 'Applying CVaR for decentralized risk management of financial companies'. Together they form a unique fingerprint.

Cite this