Modeling volatility in sector index returns with GARCH models using an iterated algorithm
Modeling volatility in sector index returns with GARCH models using an iterated algorithm
复制标题
使用迭代算法通过 GARCH 模型对行业指数回报率的波动性进行建模
DOI：
10.1007/bf02761612
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发表时间：
2004
影响因子：
--
通讯作者：
S. Hassan
中科院分区：
文献类型：
--
作者：
Farooq Malik;S. Hassan
金融市场参与者感兴趣的是，什么事件可以改变金融资产的波动模式，以及意外冲击如何决定波动随时间的持续性。本文通过使用迭代累积平方和(ICSS)算法检测波动率突变的时间周期来研究这些问题。我们考察了1992年1月至2003年8月的五个主要行业，发现在标准GARCH模型中计入波动率变化显著降低了估计的波动率持续性。我们的结果对资产定价、风险管理和投资组合选择具有重要意义。(JEL G110、G120)
Financial market participants are interested in knowing what events can alter the volatility pattern of financial assets and how unanticipated shocks determine the persistence of volatility over time. The present paper studies these issues by detecting time periods of sudden changes in volatility by using the iterated cumulated sums of squares (ICSS) algorithm. Examining five major sectors from January 1992 to August 2003, we found that accounting for volatility shifts in the standard GARCH model considerably reduces the estimated volatility persistence. Our results have important implications regarding asset pricing, risk management, and portfolio selection. (JEL G110, G120)