The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey
AbstractThe purpose of this study is to test predictive performance of Asymmetric Normal Mixture Garch (NMAGARCH) and other Garch models based on Kupiec and Christoffersen tests for Turkish equity market. The empirical results show that the NMAGARCH perform better based on %99 CI out-of-sample forecasting Christoffersen test where Garch with normal and student-t distribution perform better based on %95 Cl out-of-sample forecasting Christoffersen test and Kupiec test. These results show that none of the model including NMAGARCH outperforms other models in all cases as trading position or confidence intervals and these results shows that volatility model should be chosen according to confidence interval and trading positions. Besides, NMAGARCH increases predictive performance for higher confidence internal as Basel requires.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 2489.
Date of creation: 01 Jan 2007
Date of revision:
Garch; Asymmetric Normal Mixture Garch; Kupiec Test; Christoffersen Test; Emerging markets;
Other versions of this item:
- Atilla Çifter & Alper Özün, 2007. "The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 1(1), pages 7-34.
- G00 - Financial Economics - - General - - - General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-04-09 (All new papers)
- NEP-CWA-2007-04-09 (Central & Western Asia)
- NEP-ETS-2007-04-09 (Econometric Time Series)
- NEP-FOR-2007-04-09 (Forecasting)
- NEP-RMG-2007-04-09 (Risk Management)
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