极端价值稳定混合模型与南非股票市场指数和汇率的应用
Kimera Naradh1, Knowledge Chinhamu1, Retius Chifurira1
1School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban, South Africa.
概括
本研究评估了南非金融数据的稳定-正常-稳定 (SNS) 和稳定-核密度估计器-稳定 (SKS) 极端值混合模型. 这些模型在每日回报方面被证明是可靠的,为金融从业者提供了有价值的风险管理选择.
科学领域:
- 数量金融
- 统计模型
- 金融风险管理
背景情况:
- 极端价值组合模型在金融,保险和医疗领域越来越重要.
- 现有的模型可能无法完全捕捉独特的财务数据特征.
- 南非的金融市场面临着特殊的模拟挑战.
研究的目的:
- 评估稳定-正常-稳定 (SNS) 和稳定-核密度估计器-稳定 (SKS) 极端值混合模型的性能.
- 评估这些新型模型对南非金融数据的适用性.
- 将SNS和SKS模型与常用的极端价值混合模型进行比较.
主要方法:
- 使用SNS和SKS极值混合模型.
- 对FTSE/JSE所有股票指数 (ALSI),银行指数和采矿指数的每日回报分析.
- 分析美元/扎尔瓦尼亚卢比的汇率数据.
- 图形批量和全面的尾部模型分析.
主要成果:
- SNS和SKS混合模型在每日财务回报方面表现出强性.
- 这两种模型都有效地捕捉了分析的南非金融数据的特点.
- 这项研究证实了这些新型模型对金融应用的适用性.
结论:
- SNS和SKS模型为南非的金融建模提供了有益的方法.
- 这些模型为旨在管理风险的金融从业者提供了可靠的替代方案.
- 建议在南非金融市场进一步应用SNS和SKS模型.
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