Current students

Assessing financial model risk

Model risk has a huge impact on any financial or insurance risk measurement procedure and its quantification is therefore a crucial step. In this talk, we introduce three quantitative measures of model risk when choosing a particular reference model within a given class: the absolute measure of model risk, the relative measure of model risk and the local measure of model risk. Each of the measures has a specific purpose and so allows for flexibility. We illustrate the various notions by studying some relevant examples, so as to emphasize the practicability and tractability of our approach.

Factor Models and PCA in light of the spiked covariance model

Match making in a Kidney Paired Donation Program

Some new phenomena in high-dimensional statistics and optimization

Thursday, September 24, 2015 4:00 pm - 4:00 pm EDT (GMT -04:00)

David Sprott distinguished lecture by Raymond J. Carroll, Texas A&M University

Constrained maximum likelihood estimation for model calibration using summary-level information from external big data sources.

Information from various public and private data sources of extremely large sample

Tuesday, November 26, 2013 4:00 pm - 4:00 pm EST (GMT -05:00)

WatRISQ seminar by Steven Kou, National University of Singapore

Robust measurement of economic tail risk

We prove that the only tail risk measure that satisfies a set of economic axioms proposed by Schmeidler (1989, Econometrica) and a statistical requirement called elicitability (i.e. there exists an objective function such that a reasonable estimator must be a solution of minimizing the expected objective function) is the median shortfall, which is the median of the tail loss distribution and is also the VaR at a high confidence level.

Thursday, May 14, 2015 4:00 pm - 4:00 pm EDT (GMT -04:00)

David Sprott distinguished lecture by William Woodall, Virginia Tech

Monitoring and Improving Surgical Quality

Some statistical issues related to the monitoring of surgical quality will be reviewed in this presentation. The important role of risk-adjustment in healthcare, used to account for variations in the condition of patients, will be described. Some of the methods for monitoring quality over time, including a new one, will be outlined and illustrated with examples.