On a Statistical Criterion for the Heterogeneity of Second-Order Moments

被引：0
|
作者：
Haliullin, S. G. [1 ]
机构：
[1] Kazan Fed Univ, Lobachevsky Inst Math & Mech, Kazan 420008, Russia
来源：
RUSSIAN MATHEMATICS | 2022年 / 66卷 / 08期
关键词：
heteroscedasticity; conditionally Gaussian models; volatility;
D O I：
10.3103/S1066369X22080047
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
The presence of heteroscedasticity (heterogeneity in second-order moments) in various data leads to known errors in statistical inference if it is not noticed in time. This problem is most often encountered in the tasks of checking the adequacy of a particular model in regression or time series analysis. If the model is adequate, the residuals should be homoscedastic. In the study of the financial market, it is quite common to find heterogeneity in the second order moments in some financial indices such as logarithmic returns in stock prices. The paper considers a criterion for testing the hypothesis of homoscedasticity in statistical data.
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页码：76 / 78
页数：3
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