UWSpace is currently experiencing technical difficulties resulting from its recent migration to a new version of its software. These technical issues are not affecting the submission and browse features of the site. UWaterloo community members may continue submitting items to UWSpace. We apologize for the inconvenience, and are actively working to resolve these technical issues.
 

Computational Methods in Finance Related to Distributions with Known Marginals

Thumbnail Image

Files

Memartoluie_Amir.pdf (3.89 MB)

Date

2017-05-30

Authors

Memartoluie, Amir

Journal Title

Journal ISSN

Volume Title

Publisher

University of Waterloo

Abstract

Model uncertainty and the dependence structures of various risk factors are important components of measuring and managing financial risk, such as market, credit and operational risks. In this thesis we provide a systematic investigation into these issues by studying their impacts on Credit Value Adjustment (CVA), Counterparty Credit Risk (CCR), and estimating Value-at-Risk for a portfolio of financial instruments. In particular we address the numerical issues of finding an unknown (worst-case) copula that ties marginal distributions of risk factors together given partial information about them.

Description

Keywords

CVA, CVaR, VaR, Known Marginals, CVA contributions, Adaptive Rearrangement Algorithm, ARA, Worst-case copula, CCR, Counterparty Credit Risk, Linear Programming, Risk Management, Basel

LC Keywords

Citation

URI

http://hdl.handle.net/10012/11974

Collections

Theses
Computer Science