Post Model Correction in Risk Analysis and Management
This work focuses on Value at Risk (VaR) and Expected Shortfall (ES) in conjunction with the so called, low price effect. In order to improve forecasts of risk measures like VaR or ES when low price effect is present, we propose the low price correction which does not involve additional parameters a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Ram Arti Publishers
2019-06-01
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| Series: | International Journal of Mathematical, Engineering and Management Sciences |
| Subjects: | |
| Online Access: | https://www.ijmems.in/assets/44-ijmems-19-80-vol.-4%2c-no.-3%2c-542%E2%80%93566%2c-2019.pdf |
| _version_ | 1819047026092933120 |
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| author | G.-J. Siouris D. Skilogianni A. Karagrigoriou |
| author_facet | G.-J. Siouris D. Skilogianni A. Karagrigoriou |
| author_sort | G.-J. Siouris |
| collection | DOAJ |
| description | This work focuses on Value at Risk (VaR) and Expected Shortfall (ES) in conjunction with the so called, low price effect. In order to improve forecasts of risk measures like VaR or ES when low price effect is present, we propose the low price correction which does not involve additional parameters and instead of returns it relies on asset prices. The forecasting ability of the proposed methodology is measured by appropriately adjusted popular evaluation measures, like MSE and MAPE as well as by backtesting methods. For illustrative and comparative purposes a real example from the Athens Stock Exchange as well as a number of penny stocks from Nasdaq, NYSE and NYSE MKT are fully examined. The proposed technique is always applicable, but its superiority and effectiveness is evident in extreme economic scenarios and severe stock collapses. The proposed methodology that pays attention not only to the asset return but also to the asset price, provides sufficient evidence that prices could contain important information which could if taken under consideration, results in improved forecasts of risk estimation. |
| first_indexed | 2024-12-21T10:53:49Z |
| format | Article |
| id | doaj.art-a15efb4b290a47e19447f5ca987ca405 |
| institution | Directory Open Access Journal |
| issn | 2455-7749 2455-7749 |
| language | English |
| last_indexed | 2024-12-21T10:53:49Z |
| publishDate | 2019-06-01 |
| publisher | Ram Arti Publishers |
| record_format | Article |
| series | International Journal of Mathematical, Engineering and Management Sciences |
| spelling | doaj.art-a15efb4b290a47e19447f5ca987ca4052022-12-21T19:06:34ZengRam Arti PublishersInternational Journal of Mathematical, Engineering and Management Sciences2455-77492455-77492019-06-014354256610.33889/IJMEMS.2019.4.3-044Post Model Correction in Risk Analysis and ManagementG.-J. Siouris0D. Skilogianni1A. Karagrigoriou2Lab of Statistics and Data Analysis, Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, GreeceLab of Statistics and Data Analysis, Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, GreeceLab of Statistics and Data Analysis, Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, GreeceThis work focuses on Value at Risk (VaR) and Expected Shortfall (ES) in conjunction with the so called, low price effect. In order to improve forecasts of risk measures like VaR or ES when low price effect is present, we propose the low price correction which does not involve additional parameters and instead of returns it relies on asset prices. The forecasting ability of the proposed methodology is measured by appropriately adjusted popular evaluation measures, like MSE and MAPE as well as by backtesting methods. For illustrative and comparative purposes a real example from the Athens Stock Exchange as well as a number of penny stocks from Nasdaq, NYSE and NYSE MKT are fully examined. The proposed technique is always applicable, but its superiority and effectiveness is evident in extreme economic scenarios and severe stock collapses. The proposed methodology that pays attention not only to the asset return but also to the asset price, provides sufficient evidence that prices could contain important information which could if taken under consideration, results in improved forecasts of risk estimation.https://www.ijmems.in/assets/44-ijmems-19-80-vol.-4%2c-no.-3%2c-542%E2%80%93566%2c-2019.pdfEWMAARCHGARCHAPARCHFIGARCHExpected shortfallVaRPVaRViolation ratios; Normalised shortfallEPSLeverage effectLow price effectLow price correctionBacktesting |
| spellingShingle | G.-J. Siouris D. Skilogianni A. Karagrigoriou Post Model Correction in Risk Analysis and Management International Journal of Mathematical, Engineering and Management Sciences EWMA ARCH GARCH APARCH FIGARCH Expected shortfall VaR PVaR Violation ratios; Normalised shortfall EPS Leverage effect Low price effect Low price correction Backtesting |
| title | Post Model Correction in Risk Analysis and Management |
| title_full | Post Model Correction in Risk Analysis and Management |
| title_fullStr | Post Model Correction in Risk Analysis and Management |
| title_full_unstemmed | Post Model Correction in Risk Analysis and Management |
| title_short | Post Model Correction in Risk Analysis and Management |
| title_sort | post model correction in risk analysis and management |
| topic | EWMA ARCH GARCH APARCH FIGARCH Expected shortfall VaR PVaR Violation ratios; Normalised shortfall EPS Leverage effect Low price effect Low price correction Backtesting |
| url | https://www.ijmems.in/assets/44-ijmems-19-80-vol.-4%2c-no.-3%2c-542%E2%80%93566%2c-2019.pdf |
| work_keys_str_mv | AT gjsiouris postmodelcorrectioninriskanalysisandmanagement AT dskilogianni postmodelcorrectioninriskanalysisandmanagement AT akaragrigoriou postmodelcorrectioninriskanalysisandmanagement |