The Local Whittle Estimator of Long Memory Stochastic Volatility
The Local Whittle Estimator of Long Memory Stochastic Volatility
复制标题
长记忆随机波动率的局部Whttle估计
DOI：
10.1093/jjfinec/nbg018
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
B. Ray
中科院分区：
文献类型：
--
作者：
Clifford M. Hurvich;B. Ray
提出了一种新的长记忆随机波动率（LMSV）模型波动持续性程度的半参数估计。估计器使用的周期图的对数平方返回在一个本地Whittle标准，明确占LMSV模型中的噪声项。提供了估计量的随机样本和渐近标准误差。一个广泛的模拟研究表明，当地的Whittle估计是少得多的偏见和有限样本的标准误产生更准确的置信区间比广泛使用的GPH估计。估计也被发现是强大的对可能的杠杆效应。在对每日德国马克/美元汇率的实证分析中，新的估计量表明，如果使用大量的频率，则波动的持续性比GPH估计量更强。, .
We propose a new semiparametric estimator of the degree of persistence in volatility for long memory stochastic volatility (LMSV) models. The estimator uses the periodogram of the log squared returns in a local Whittle criterion which explicitly accounts for the noise term in the LMSV model. Finite-sample and asymptotic standard errors for the estimator are provided. An extensive simulation study reveals that the local Whittle estimator is much less biased and that the finite-sample standard errors yield more accurate confidence intervals than the widely-used GPH estimator. The estimator is also found to be robust against possible leverage effects. In an empirical analysis of the daily Deutsche Mark/US Dollar exchange rate, the new estimator indicates stronger persistence in volatility than the GPH estimator, provided that a large number of frequencies is used. , .