首页> 外文期刊>Asia-Pacific Journal of Financial Studies >Modeling and Forecasting Realized Volatilities of Korean Financial Assets Featuring Long Memory and Asymmetry
【24h】

Modeling and Forecasting Realized Volatilities of Korean Financial Assets Featuring Long Memory and Asymmetry

机译:具有长记忆和不对称性的韩国金融资产已实现波动率的建模和预测

获取原文
获取原文并翻译 | 示例
           

摘要

Long memory, asymmetry, volatility spillover aspects of the realized volatilities (RVs) of the log returns of the Korean KOSPI, the Korean won/US dollar exchange rate, Korean treasury bond futures, and the US S&P 500 index are investigated in this paper. For all RVs, significant long memories and asymmetries are identified, which can improve forecasts if suitably used. A new long memory asymmetric threshold HAR-RV (heteroskedastic autoregressive realized volatility) model is proposed. The new model shows explicit differences between the coefficients of daily, weekly, and monthly RVs for days of positive returns and those for days of negative returns. By analyzing the RVs, we find that pseudo out-of-sample forecast performance of the proposed model is better than a widely used existing asymmetric long memory model in about half of cases considered. The new model as well as another existing asymmetric model show that forecast improvements due to implied volatilities for the S&P 500 index decrease when asymmetries in RVs are accounted for. The two asymmetric models find significant decompositions of the spillover effects from the influential market S&P 500 index to the influenced market KOSPI (or from the KOSPI to the Korean won/US dollar exchange rate) into three oscillating components: substantial positive short-term daily spillovers, moderate negative weekly spillovers, and somewhat positive long-term monthly spillovers.
机译:本文研究了韩国KOSPI原木收益率的已实现波动率(RVs)的长记忆,不对称性,波动率溢出方面,韩元/美元汇率,韩国国债期货以及美国S&P 500指数。对于所有RV,可以识别出很长的记忆和不对称性,如果使用得当,可以改善预测。提出了一种新的长记忆非对称阈值HAR-RV(异方差自回归实现的波动性)模型。新模型显示了在正收益日和负收益日的每日,每周和每月RV系数之间的显着差异。通过分析RV,我们发现,在考虑的一半情况下,该模型的伪样本外预测性能优于广泛使用的现有非对称长记忆模型。新模型以及另一个现有的非对称模型表明,考虑到RV中的非对称性,由于S&P 500指数的隐含波动率导致的预测改进会减少。两种不对称模型发现,从有影响力的市场标准普尔500指数到受影响的市场KOSPI(或从KOSPI到韩元/美元汇率)的溢出效应分解为三个振荡成分:短期正每日大幅溢出,适度的负每周溢出和长期正每月溢出。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号