Monte-Carlo Estimation of CoVaR

2022/10/12 by Huang, Weihuan, Lin, Nifei, Hong, L. Jeff · 1 citation
#FOS: Economics and business #Risk Management (q-fin.RM)

paper · doi:10.48550/arxiv.2210.06148

Abstract

\rm CoVaR is one of the most important measures of financial systemic risks. It is defined as the risk of a financial portfolio conditional on another financial portfolio being at risk. In this paper we first develop a Monte-Carlo simulation-based batching estimator of CoVaR and study its consistency and asymptotic normality. We show that the optimal rate of convergence of the batching estimator is n^-1/3, where n is the sample size. We then develop an importance-sampling inspired estimator under the delta-gamma approximations to the portfolio losses, and we show that the rate of convergence of the estimator is n^-1/2. Numerical experiments support our theoretical findings and show that both estimators work well.

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