Monte Carlo estimation of economic capital
Document Type
Conference Proceeding
Publication Date
7-2-2018
Abstract
Economic capital (EC) is a risk measure that has been used by financial firms to help determine capital levels to hold to protect (with high probability) against large unexpected losses of credit portfolios. Given a stochastic model for a portfolio's loss over a given time horizon, the EC is defined as the difference between a quantile and the mean of the loss distribution. We describe Monte Carlo methods for estimating the EC. We apply measure-specific importance sampling to separately estimate the two components of the EC, which can lead to much smaller variance than when estimating both terms simultaneously. We provide Bahadur-type representations for our estimators of the EC, which we further exploit to establish central limit theorems and asymptotically valid confidence intervals. We present numerical results for a simple model to demonstrate the effectiveness of our approaches.
Identifier
85062601784 (Scopus)
ISBN
[9781538665725]
Publication Title
Proceedings Winter Simulation Conference
External Full Text Location
https://doi.org/10.1109/WSC.2018.8632308
ISSN
08917736
First Page
1754
Last Page
1765
Volume
2018-December
Grant
CMMI-1537322
Fund Ref
National Science Foundation
Recommended Citation
Kaplan, Zachary T.; Li, Yajuan; and Nakayama, Marvin K., "Monte Carlo estimation of economic capital" (2018). Faculty Publications. 8529.
https://digitalcommons.njit.edu/fac_pubs/8529
