Measuring Risk utilizing Credible Monte Carlo Value at Risk and Credible Monte Carlo Expected Tail Loss
This paper proposes two new methods to measure the risk of individual stocks, which construct a portfolio, namely Credible Monte Carlo Value at Risk (CMC VaR) and Credible Monte Carlo Expected Tail Loss (CMC ETL). The CMC VaR is developed by combining the concept of Credible Value at Risk (Cr V...
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| Main Authors: | , , |
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| Format: | Other NonPeerReviewed |
| Language: | English |
| Published: |
IAENG International Journal of Applied Mathematics
2022
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| Subjects: | |
| Online Access: | https://repository.ugm.ac.id/284235/1/IJAM_52_1_31.pdf https://repository.ugm.ac.id/284235/ https://efaidnbmnnnibpcajpcglclefindmkaj/https://www.iaeng.org/IJAM/issues_v52/issue_1/IJAM_52_1_31.pdf |
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| Summary: | This paper proposes two new methods to measure
the risk of individual stocks, which construct a portfolio, namely
Credible Monte Carlo Value at Risk (CMC VaR) and Credible
Monte Carlo Expected Tail Loss (CMC ETL). The CMC VaR is
developed by combining the concept of Credible Value at Risk
(Cr VaR) with Monte Carlo VaR (MC VaR). Meanwhile, CMC
ETL is constructed by mixing Credible ETL (Cr ETL) and MC
ETL. The new method’s performance is empirically verified
to evaluate the individual risk of each asset developing three
portfolios. The analyzed portfolios are designed by Indonesian
five stocks indexed by LQ 45, four stocks traded in New York
Stock Exchange (NYSE), two stocks indexed by NASDAQ, and
two stocks indexed by London Stock Exchange. We also assess
the accuracy of the CMC VaR by Kupiec Backtesting. The
empirical results of this paper implied that two novel methods
are effective in measuring the risk at 80 percent, 90 percent,
and 95 percent confidence levels. The proposed methods can
also overcome the drawback of VaR and ETL, which do not
contemplate the risk among assets grouped in a portfolio. |
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