A Sequential Importance Sampling for Estimating Multi-Period Tail Risk
Plain or crude Monte Carlo simulation (CMC) is commonly applied for estimating multi-period tail risk measures such as value-at-risk (VaR) and expected shortfall (ES). After fitting a volatility model to the past history of returns and estimating the conditional distribution of innovations, one can...
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Main Authors: | Ye-Ji Seo, Sunggon Kim |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
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Series: | Risks |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-9091/12/12/201 |
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