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 the real implications of these results for Value-at-Risk estimation is 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 InfoArticle provided by Banking Regulation and Supervision Agency in its journal Journal of Banking and Financial Markets.
Volume (Year): 1 (2007)
Issue (Month): 1 ()
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More information through EDIRC
GARCH; Asymmetric Normal Mixture GARCH; Christoffersen Test; Emerging Markets.;
Other versions of this item:
- Cifter, Atilla & Ozun, Alper, 2007. "The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey," MPRA Paper 2489, University Library of Munich, Germany.
- 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
- G0 - Financial Economics - - General
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