Matrix Variate Distributions as a Tool for Insurers and their Application to Natural Hazard Loss Modeling Matrix Variate Distributions as a Tool for Insurers and their Application to Natural Hazard Loss Modeling A growing number of insurance problems require modeling the distributions of random matrices. The most commonly used of such distributions within the nance and actuarial literature is the Wishart distribution , which arises as the distribution of the sample covariance matrix of a multivariate normal dataset. The Wishart distribution has widely been applied in insurance and nance problems such as portfolio analysis , time series analysis , and rate making . However, many other matrix variate distributions exist, such as the matrix variate normal and matrix variate t distributions, and their use has not been explored yet within the actuarial domain.
|Effective start/end date||7/8/21 → 7/7/24|
- Casualty Actuarial Society (CAS): $17,000.00
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.