Loglinear Model Review

It has been widely studied how investors will allocate their assets to an investment when the return of assets is normally distributed. In this context usually, the problem of portfolio optimization is analyzed using mean-variance. When asset returns are not normally distributed, the mean-variance analysis may not be appropriate for selecting the optimum portfolio. This paper will examine the consequences of abnormalities in the process of allocating investment portfolio assets. Here will be shown how to adjust the mean-variance standard as a basic framework for asset allocation in cases where asset returns are not normally distributed. We will also discuss the application of the optimum strategies for this problem. Based on the results of literature studies, it can be concluded that the expected utility approximation involves averages, variances, skewness, and kurtosis, and can be extended to even higher moments.

Download Full-text

Review Plan Using the NWD Model Review Plan for Continuing Authorities Program Section 14, 107, 111, 204, 206, 208, 1135 and Projects Directed by Guidance to Use CAP Procedures: Sheridan, Wyoming, Section 1135 Project

10.21236/ada627130 ◽

2014 ◽

Author(s):

CORPS OF ENGINEERS OMAHA NE

Keyword(s):

Model Review

Download Full-text

Loglinear Model Formation using Hierachial Backward Method

Journal of Research in Mathematics Trends and Technology ◽

10.32734/jormtt.v2i1.3754 ◽

2020 ◽

Vol 2 (1) ◽

pp. 28-36

Author(s):

Siti Fatimah Sihotang ◽

Zuhri

Keyword(s):

Linear Model ◽

Good Method ◽

General Linear Model ◽

Loglinear Model ◽

Complete Model ◽

The Third ◽

Several Variables ◽

Model Formation ◽

Special Case ◽

Categorical Scale

The loglinear model is a special case of a general linear model for poissondistributed data. The loglinear model is also a number of models in statistics that are used todetermine dependencies between several variables on a categorical scale. The number ofvariables discussed in this study were three variables. After the variables are investigated,the formation of the loglinear model becomes important because not all the modelinteraction factors that exist in the complete model become significant in the resultingmodel. The formation of the loglinear model in this study uses the Backward Hierarchicalmethod. This research makes loglinear modeling to get the model using the HierarchicalBackward method to choose a good method in making models with existing examples.From the challenging examples that have been done, it is known that the HierarchicalReverse method can model the third iteration or scroll. Then, also use better assessmentmethods about faster workmanship and computer-sponsored assessments that are used moreefficiently through compatibility testing for each model made

Download Full-text