@inproceedings{ea6fda781af64f328ce8678adbafaa49,
title = "Monte Carlo estimation of economic capital",
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.",
author = "Kaplan, {Zachary T.} and Yajuan Li and Nakayama, {Marvin K.}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE; 2018 Winter Simulation Conference, WSC 2018 ; Conference date: 09-12-2018 Through 12-12-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/WSC.2018.8632308",
language = "English (US)",
series = "Proceedings - Winter Simulation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1754--1765",
booktitle = "WSC 2018 - 2018 Winter Simulation Conference",
address = "United States",
}