Abstract
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 language | English (US) |
|---|---|
| Pages (from-to) | 627-644 |
| Number of pages | 18 |
| Journal | Journal of Banking and Finance |
| Volume | 30 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 2006 |
All Science Journal Classification (ASJC) codes
- Finance
- Economics and Econometrics
Keywords
- Conditional value-at-risk
- Decentralized optimization
- Risk management
- Risk measures
- Utility optimization