Fixed Point Result on Generalized Cone b-Metric Spaces
Zaheer Kareem Ansari,
Ajay Kumar Singh,
Pawan Kumar,
Jay Prakash Patel
Issue:
Volume 11, Issue 2, April 2022
Pages:
28-32
Received:
8 February 2022
Accepted:
10 March 2022
Published:
31 March 2022
Abstract: The purpose of this paper is to prove a fixed point result on contraction mapping in generalized cone b-metric space (in short GCbMS) as a generalization of cone metric space, cone b metric space and rectangular metric space. The conception of generalized metric space is a generalization of that of classical metric space. Several authors have proved fixed point theorems of contractive mappings on generalized metric spaces, which also generalized some corresponding fixed point results in classical metric spaces. In present paper, we prove a result that is extension of the Kannan fixed point theorem proved by Reny George et al. Our result is extend and unify several well known results in the literature available for cone and cone-b metric space.
Abstract: The purpose of this paper is to prove a fixed point result on contraction mapping in generalized cone b-metric space (in short GCbMS) as a generalization of cone metric space, cone b metric space and rectangular metric space. The conception of generalized metric space is a generalization of that of classical metric space. Several authors have prove...
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Frequency Domain Analysis of Nigeria All Share and Capital Index from 1989-2010 (A Case Study of Nigerian Stock Market)
Aideyan Donald Osaro,
Usman Suleiman
Issue:
Volume 11, Issue 2, April 2022
Pages:
33-38
Received:
12 February 2022
Accepted:
3 March 2022
Published:
7 May 2022
Abstract: In recent years the method of wavelet analysis has been opened to researchers. It is the analyses of data at different level of decomposition and can capture the characteristics of data series in all decomposition level. In this research work, data was collected on the Nigerian stock index for All Share and Capital market indexes (1989-2010). The data were analyzed by wavelet method to detect the aberrant observations (AOs) over the period under study for the two indexes. Akaike information criterion (AIC) was also used to detect the ‘best model’ for the two indexes using some distributions. A total of seventeen and eleven AOs were detected from the original data collected on All Share and Capital Market indexes respectively. In the first, second and third resolutions, a total of four, two and two AOs were detected from the All Share index, while a total of five, four and three AOs were detected from that of Capital Market index. The results obtained showed the AOs detected in the analysis of the original data maintain the same or closely the same positions as that obtained from the analysis of the decomposed data for the two stock indexes. It was observed that the index of stocks in March, July and December are more and less in February, March, and November for the two indexes. The AIC results show that, the Cauchy distribution has the smallest AIC values among the distributions used, which means is the ‘best model’.
Abstract: In recent years the method of wavelet analysis has been opened to researchers. It is the analyses of data at different level of decomposition and can capture the characteristics of data series in all decomposition level. In this research work, data was collected on the Nigerian stock index for All Share and Capital market indexes (1989-2010). The d...
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