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Researcher | Institution | Original publication | Reading recommendations | Beyond | CitationThe paper presented in this video, from the field of financial mathematics, addresses the problem of building optimal loan portfolios and develops a novel computational method to do so even if with an infinite number of loans. The new tool was tested on a data-set of 120 million mortgage loans, and was able to solve this high-dimensional problem. As KAY GIESECKE explains, the applied method is an asymptotic approximation approach: To solve the problem at hand, the solution to a problem with fewer dimensions is computed, and as the portfolio grows larger again, the solution “grows” into the solution of the actual problem.
DOI:
https://doi.org/10.21036/LTPUB10111
Institution
Stanford University
"Stanford University, located between San Francisco and San Jose in the heart of California's Silicon Valley, is one of the world's leading teaching and research universities. Since its opening in 1891, Stanford has been dedicated to finding solutions to big challenges and to preparing students for leadership in a complex world." ( Source )
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Original publication
Large-Scale Loan Portfolio Selection
Stanford University
Published in 2016
Reading recommendations
Large Portfolio Asymptotics for Loss From Default
Mathematical Finance
Published in 2015
Risk Analysis for Large Pools of Loans
Working Paper
Published in 2015
Fluctuation Analysis for the Loss From Default
Stochastic Processes and their Applications
Published in 2014
Default Clustering in Large Portfolios: Typical Events
The Annals of Applied Probability
Published in 2013
Beyond
A Ground-breaking Scientific Revolution
An Alarming Challenge for Society
If I Had a Second Life
A Personal Reading Recommendation