A wavelet Whittle estimator of generalized long-memory stochastic volatility

Alex Gonzaga; Michael Hauser

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A wavelet Whittle estimator of generalized long-memory stochastic volatility

机译：广义长记忆随机波动率的小波Whittle估计

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We consider a k-GARMA generalization of the long-memory stochastic volatility model, discuss the properties of the model and propose a wavelet-based Whittle estimator for its parameters. Its consistency is shown. Monte Carlo experiments show that the small sample properties are essentially indistinguishable from those of the Whittle estimator, but are favorable with respect to a wavelet-based approximate maximum likelihood estimator. An application is given for the Microsoft Corporation stock, modeling the intraday seasonal patterns of its realized volatility.

机译：我们考虑了长记忆随机波动率模型的k-GARMA推广，讨论了模型的性质，并提出了基于小波的Whittle估计器。显示其一致性。蒙特卡洛实验表明，小样本属性与Whittle估计器的性质基本没有区别，但是相对于基于小波的近似最大似然估计器而言，这是有利的。为Microsoft Corporation股票提供了一个应用程序，它模拟了其已实现波动的日内季节性模式。

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来源
《Statistical Methods and Applications》 |2011年第1期|p.23-48|共26页
作者
Alex Gonzaga; Michael Hauser;
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作者单位

Department of Physical Sciences and Mathematics, University of the Philippines, Padre Faura St., Manila, Philippines,Department of Statistics and Mathematics, Wirschaftsuniversitat Wien, Augasse 2-6, 1090 Vienna, Austria;

rnDepartment of Statistics and Mathematics, Wirschaftsuniversitat Wien, Augasse 2-6, 1090 Vienna, Austria;

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原文格式 PDF
正文语种 eng
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关键词
long-memory; k-GARMA; stochastic volatility; whittle estimator; wavelets;

机译：长记忆k-GARMA;随机波动;估算器小波;

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1. THE SLOW CONVERGENCE OF ORDINARY LEAST SQUARES ESTIMATORS OF α,β AND PORTFOLIO WEIGHTS UNDER LONG-MEMORY STOCHASTIC VOLATILITY [J] . Liu Jun, Deo Rohit, Hurvich Clifford Journal of Time Series Analysis . 2019,第4期

机译：长记忆随机波动下α，β和投资组合权重的最小二乘估计的慢收敛性
2. THE SLOW CONVERGENCE OF ORDINARY LEAST SQUARES ESTIMATORS OF α,β AND PORTFOLIO WEIGHTS UNDER LONG-MEMORY STOCHASTIC VOLATILITY [J] . Liu Jun, Deo Rohit, Hurvich Clifford Journal of Time Series Analysis . 2019,第4期

机译：在长记忆随机挥发性下α，β和组合重量的普通最小二乘估计的缓慢收敛性
3. Applicability of the Whittle estimator to non-stationary and non-linear long-memory processes [J] . Sousa-Vieira M. E. Journal of simulation . 2016,第3期

机译：Whittle估计器对非平稳和非线性长存储过程的适用性
4. Seasonal Long-memory Stochastic Volatility [C] . Alex C. Gonzaga International Conference of Numerical Analysis and Applied Mathematics . 2014

机译：季节性长记忆随机波动率
5. Econometric essays on generalized empirical likelihood, long-memory time series, and volatility. [D] . Guggenberger, Patrik. 2003

机译：关于广义经验似然，长记忆时间序列和波动性的计量经济学文章。
6. Bayesian analysis of stochastic volatility-in-mean model with leverage and asymmetrically heavy-tailed error using generalized hyperbolic skew Student’s t-distribution [O] . William L. Leão, Carlos A. Abanto-Valle, Ming-Hui Chen -1

机译：使用广义双曲斜学生t分布的具有杠杆和不对称重尾误差的随机均值波动模型的贝叶斯分析
7. The local Whittle estimator of long-memory stochastic volatility [O] . Clifford M. Hurvich 2003

机译：长期随机波动率的本地Whittle估计
8. Allan Variance as an Estimator of the Long-Memory Parameter: Time- Domain and Wavelet Methods [R] . Schmidt, L. S. , Skinner, J. G. 2005

机译：allan Variance作为长记忆参数的估计：时域和小波方法

A wavelet Whittle estimator of generalized long-memory stochastic volatility

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