This paper uses the estimation of the Self-Excited Multi Fractal (SEMF) model, which holds theoretical promise but has seen mixed results in practice, as a case study to explore the impact of distributional assumption...This paper uses the estimation of the Self-Excited Multi Fractal (SEMF) model, which holds theoretical promise but has seen mixed results in practice, as a case study to explore the impact of distributional assumptions on the model fitting process. In the case of the SEMF model, this examination shows that incorporating reasonable distributional assumptions including a non-zero mean and the leptokurtic Student’s t distribution can have a substantial impact on the estimation results and can mean the difference between parameter estimates that imply unstable and potentially explosive volatility dynamics versus ones that describe more reasonable and realistic dynamics for the returns. While the original SEMF model specification is found to yield unrealistic results for most of the series of financial returns to which it is applied, the results obtained after incorporating the Student’s t distribution and a mean component into the model specification suggest that the SEMF model is a reasonable model, implying realistic return behavior, for most, if not all, of the series of stock and index returns to which it is applied in this study. In addition, reflecting the sensitivity of the sample mean to the types of characteristics that the SEMF model is designed to capture, the results of this study also illustrate the value of incorporating the mean component directly into the model and fitting it in conjunction with the other model parameters rather than simply centering the returns beforehand by subtracting the sample mean from them.展开更多
配电网受谐波和噪声干扰严重,电压相量的计算难度更大,传统的输电网相量测量精度不能满足配电网的要求。为提高配电网电压相量幅值和相角的测量精度,提出了一种基于条件最大似然估计法(conditional maximum likelihood estimation,CML)...配电网受谐波和噪声干扰严重,电压相量的计算难度更大,传统的输电网相量测量精度不能满足配电网的要求。为提高配电网电压相量幅值和相角的测量精度,提出了一种基于条件最大似然估计法(conditional maximum likelihood estimation,CML)的配电网微型同步相量测量单元(μPMU)的相量测量方法。该算法建立了三相不平衡系统的信号模型,在待测量最多包含两个未知量且待测量矩阵与单位矩阵正交不等于零时,利用三相矩阵与样本协方差矩阵的特征向量正交来获取待测量,进而通过几何特性推导出电压相量的幅值及相位表达式,降低了运算量。通过Matlab进行了仿真验证,仿真结果表明所提方法能够在一定程度上提高配电网电压相量幅值和相位的测量精度。展开更多
文摘This paper uses the estimation of the Self-Excited Multi Fractal (SEMF) model, which holds theoretical promise but has seen mixed results in practice, as a case study to explore the impact of distributional assumptions on the model fitting process. In the case of the SEMF model, this examination shows that incorporating reasonable distributional assumptions including a non-zero mean and the leptokurtic Student’s t distribution can have a substantial impact on the estimation results and can mean the difference between parameter estimates that imply unstable and potentially explosive volatility dynamics versus ones that describe more reasonable and realistic dynamics for the returns. While the original SEMF model specification is found to yield unrealistic results for most of the series of financial returns to which it is applied, the results obtained after incorporating the Student’s t distribution and a mean component into the model specification suggest that the SEMF model is a reasonable model, implying realistic return behavior, for most, if not all, of the series of stock and index returns to which it is applied in this study. In addition, reflecting the sensitivity of the sample mean to the types of characteristics that the SEMF model is designed to capture, the results of this study also illustrate the value of incorporating the mean component directly into the model and fitting it in conjunction with the other model parameters rather than simply centering the returns beforehand by subtracting the sample mean from them.
文摘配电网受谐波和噪声干扰严重,电压相量的计算难度更大,传统的输电网相量测量精度不能满足配电网的要求。为提高配电网电压相量幅值和相角的测量精度,提出了一种基于条件最大似然估计法(conditional maximum likelihood estimation,CML)的配电网微型同步相量测量单元(μPMU)的相量测量方法。该算法建立了三相不平衡系统的信号模型,在待测量最多包含两个未知量且待测量矩阵与单位矩阵正交不等于零时,利用三相矩阵与样本协方差矩阵的特征向量正交来获取待测量,进而通过几何特性推导出电压相量的幅值及相位表达式,降低了运算量。通过Matlab进行了仿真验证,仿真结果表明所提方法能够在一定程度上提高配电网电压相量幅值和相位的测量精度。
