Normal correlation.

2011 ◽  
pp. 317-334
Author(s):  
G. Udny Yule
Keyword(s):  
2021 ◽  
Vol 29 (1) ◽  
pp. 50-66
Author(s):  
Shafiu Ibrahim Abdullahi

PurposeThe purpose of the study is to measure cross-country stock market correlation and volatility transmission during the global coronavirus disease 2019 (COVID-19) pandemic. The paper traces trajectory of Islamic equity investments in order to get insights on the behavior of the markets during the crisis.Design/methodology/approachThe paper uses generalized method of moments (GMM), autoregressive distributed lag (ARDL) and multivariate GARCH (MGARCH) models for analysis of dynamic causality, stock market cointegration, correlation and volatility transmission between Islamic stock indices.FindingsThe result of normal correlation analysis on the share indices show the markets move together. The result of ARDL cointegration test shows the markets returns are cointegrated as a group. To further make sense of the data; the indices were grouped into four different categories, then cointegration tests were conducted. The results of the analysis show that the subgroups are cointegrated except the low COVID-19 subgroup. Based on MGARCH findings, the possibility of volatility transmission between markets during the crisis is high. The market returns indices show the usual herd mentality common during the period of crisis.Originality/valueUnlike other works in this area, this paper attempt to trace the trajectory of Islamic equity investment in order to get relevant insights and arrives at appropriate ways of responding to the crisis.


1979 ◽  
Vol 74 (368) ◽  
pp. 815 ◽  
Author(s):  
Julian Kollerstrom ◽  
G. Barrie Wetherill

1979 ◽  
Vol 74 (368) ◽  
pp. 815-821
Author(s):  
Julian Köllerström ◽  
G. Barrie Wetherill

(1) In earlier memoirs by one of the present authors, methods have been discussed for the calculation of the constants ( a ) of variation, normal or skew, ( b ) of correla­tion, when normal. The subject of skew correlation would now naturally present itself, but although several important conclusions with regard to skew correlation have been worked out, there are still difficulties which impede the completion of the memoir on that topic. Meanwhile Mr. G. U. Yule has shown that the constants of normal correlation are significant, if not completely descriptive, even in the case of skew correlation. It seems desirable to take, some what out of its natural order, the subject of the present memoir, partly because the formulæ involved have been once or twice cited and several times used in memoirs by one of the present writers, and partly because the need of such formulæ seems to have been disregarded by various authors in some what too readily drawing conclusions from statistical data. Differences in the constants of variation or of correlation have been not infrequently asserted to be significant or non-significant of class or of type, or of race differences, without a due investigation of whether those differences are, from the standpoint of mathematical statistics, greater or less than the probable errors of the differences. Not withstanding that every artificial or even random selection of a group out of a community changes not only the amount of variation, but the amount of correlation of the organs of its members as com pared with those of the primitive group, it has been supposed that correlation might be a racial constant, and the approximate constancy of coefficients of correlation of the same organs in allied species has been used as a valid argument. In the like manner differences in variation have been used as an argument for the activity of natural selection without a discussion of the probable errors of those differences. In dealing with variation and correlation we find the distribution described by certain curves or surfaces fully determined when certain constants are known. These are the so-called constants of variation and correlation, the number of which may run up from two to a very considerable figure in the case of a complex of organs. If we deal with a complex of organs in two groups containing, say, n and n ' individuals, we can only ascertain whether there is a significant or insignificant difference between those groups by measuring the extent to which the differences of corresponding constants exceed the probable errors of those differences. The probable error of a difference can at once be found by taking the square root of the sum of the squares of the probable errors of the quantities forming the difference. Hence the first step towards determining the significance of a group difference— i. e ., towards ascertaining whether it is really a class, race, or type difference— is to calculate the probable errors of the constants of variation and correlation of the individual groups. This will be the object of our first general theorem.


2012 ◽  
pp. 313-330
Author(s):  
G. Undy Yule
Keyword(s):  

1898 ◽  
Vol 62 (379-387) ◽  
pp. 170-173 ◽  

The object of the paper is, in the first place, to simplify and extend the treatment of normal correlation as expounded by Francis Galton and Karl Pearson; and in the second place to obtain general formuIæ in the theory of error, and to apply them to questions which arise in relation to normal distributions and normal correlation. The method is, throughout, elementary, the use of the differential and integral calculus being avoided, though geometrical infinitesimals are to a certain extent employed.


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