Abdul-Lateef Haji-Ali - Sub-sampling and other considerations for efficient risk estimation in large portfolios
|Starts:||12:00 22 Oct 2019|
|Ends:||13:00 22 Oct 2019|
|What is it:||Seminar|
|Organiser:||Department of Mathematics|
|Who is it for:||University staff, External researchers, Current University students|
|Speaker:||Dr Abdul-Lateef Haji-Ali|
Join us for this research seminar, part of the SQUIDS (Statistics, quantification of uncertainty, inverse problems and data science) seminar series.
Abstract: Computing risk measures of a financial portfolio comprising thousands of options is a challenging problem because (a) it involves a nested expectation requiring multiple evaluation of the loss of the financial portfolio for different risk scenarios and (b) evaluating the loss of the portfolio is expensive and the cost increases with its size. In this talk, I look at applying Multilevel Monte Carlo (MLMC) with adaptive inner sampling to this problem and discuss several practical considerations. In particular, I will discuss a sub-sampling strategy that results in a method whose computational complexity does not increase with the size of the portfolio. I will also talk about several control variates that significantly improve the efficiency of MLMC in the current setting.
Dr Abdul-Lateef Haji-Ali
Role: Assistant Professor - Actuarial Mathematics and Statistics
Organisation: Heriot-Watt University
Travel and Contact Information
Frank Adams 1
Alan Turing Building