Non-Parametric Robust Model Risk Measurement with Path-Dependent Loss Functions
Mathematical Finance
2019-03-06 v1 Portfolio Management
Abstract
Understanding and measuring model risk is important to financial practitioners. However, there lacks a non-parametric approach to model risk quantification in a dynamic setting and with path-dependent losses. We propose a complete theory generalizing the relative-entropic approach by Glasserman and Xu to the dynamic case under any -divergence. It provides an unified treatment for measuring both the worst-case risk and the -divergence budget that originate from the model uncertainty of an underlying state process.
Cite
@article{arxiv.1903.00590,
title = {Non-Parametric Robust Model Risk Measurement with Path-Dependent Loss Functions},
author = {Yu Feng},
journal= {arXiv preprint arXiv:1903.00590},
year = {2019}
}