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

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