African Scientific Annual Review

Forecasting Financial Crisis using Topological Data Analysis Approach

2024-07-02T07:37:46+00:00

Traditional financial forecasting methods often struggle to capture the complex interactions and emerging patterns that precede financial crises. By leveraging on TDA, this research aims to uncover potential topological features that might serve as early warning signals for impending financial crises. The study adopts the utilization of Topological Data Analysis, an initiative mathematical framework to explore and analyze the inherent topological structures within financial data set, using secondary data from ”Yahoo Finance API”. The results of the analysis conducted using Python indicate that persistence homology in TDA successfully identifies key topology features associated with financial crises, implying its potential for developing early warning systems in the financial sector. The insights gained from this analysis could significantly enhance the early detection and proactive management of system risks in financial market, thereby contributing to more robust risk assessment and policy formulation strategies.

On Some Aspects of Compactness in Metric Spaces

2024-07-02T07:42:55+00:00

In this paper, we investigate the generalizations of the concepts from Heine-Borel Theorem and the Bolzano-Weierstrass Theorem to metric spaces. We show that the metric space X is compact if every open covering has a finite subcovering. This abstracts the Heine-Borel property. Indeed, the Heine-Borel Theorem states that closed bounded subsets of the real line R are compact. In this study, we rephrase compactness in terms of closed bounded subsets of the real line R, that is, the Bolzano-Weierstrass theorem. Let X be any closed bounded subset of the real line. Then any sequence (xn) of the points of X has a subsequence converging to a point of X. We have used these interesting theorems to characterize compactness in metric spaces.

Regression Analysis of the Effects of Debt on Economic Performance in Kenya

2024-07-02T07:47:42+00:00

This study investigates the impact of debt on economic performance in Kenya, focusing on both internal and external debt. Using regression analysis and correlation techniques, data from 2000 to 2021 was analyzed to understand the relationship between debt levels and economic growth indicators such as GDP. The findings reveal a nuanced relationship: while internal debt shows a positive association with economic growth, external debt demonstrates a negative association. Effective debt management strategies are crucial to mitigate adverse effects, including monitoring debt levels, negotiating favorable terms with creditors, and directing borrowing towards productive sectors. Promoting export-led growth, enhancing fiscal discipline, and continuous monitoring and evaluation are recommended policy actions. Despite limitations such as data constraints and external factors influencing economic performance, future research avenues include long-term analysis, sectoral studies, comparative analyses, and qualitative investigations into stakeholder perceptions. This study contributes to understanding the complexities of debt dynamics and informs policymakers in navigating sustainable economic development pathways.

Analyzing the Relationship between Government Revenue and Economic Growth in Kenya from 2012-2022 using Multiple Linear Regression

2024-07-02T07:53:18+00:00

The relationship between government revenue and economic growth is a debate that has existed for a long time in the living history.Government revenue impacts economic growth differently within different regions. Some researchers argue that government revenue positively affects economic growth while others argue that the relationship is negative. However, minimal literature exists exploring the relationship between the two variables at country specific level. The objective of this study was to determine the relationship between Government revenue and economic growth in Kenya. The research adopted the correlational study design. The study used secondary data collected from the Central Bank of Kenya, KNBS, and Government records such as the finance Act. We collected data on different sources of Government Revenue such income tax, Value Added Tax (VAT), excise duty, import duty, Other tax income. The study also included data on non-tax revenue. The set of data under the study was from the financial years 2011/2012 to 2022/2023. The analysis has been done by the use of R software. To identify the level of association of the study variables such as GDP,Income tax,VAT,excise tax,import duty,other tax and non-tax revenue, he study employs multiple linear regression analysis. To check on the level of significance, we tested at 5% significant levels. The p-value is 0.008462 which was less than 0.05 hence we reject the null hypothesis and conclude that there is significant positive relationship between Government Revenue and Economic growth in Kenya.

Numerical Solutions of Potential Flow Equations using Finite Differences

2024-07-02T08:00:29+00:00

This article delves into the numerical solutions of potential flow equations using finite differences, aiming to enhance our understanding of fluid dynamics. The general objective is to obtain numerical solutions to potential flow equations using finite differences, with specific objectives including the investigation of potential flow equations, the solutions of associated PDE and the analysis of the stability of employed numerical schemes. The study employs a combination of numerical methods to achieve its objectives; MATLAB is utilized as a computational tool, while the Gauss-Seidel and Jacobi’s iterative methods are implemented for solving PDEs. Central differences are employed for discretization. The study yields valuable insights into the behaviour of potential flow systems. The significance of this research lies in its contribution to advancing our comprehension of fluid dynamics with potential applications. Generally, this work provides a foundation for further exploration and application of numerical methods in the study of potential flow.

Predicting Rainfall Pattern in Kakamega County using Time Series

2024-07-02T08:08:32+00:00

Rainfall patterns play a critical role in shaping various aspects of our lives. Understanding the patterns, trends and predictability of rainfall is essential for effective planning and decision making in various aspects including agriculture, water resource management, disaster preparedness and social economic planning. In agricultural activities crops require specific amount of water at the right time for growth. By understanding the rainfall patterns, farmers can adapt their farming activities, optimizing irrigation strategies and make informed decisions. In the management, it help policy makers and management authorities for planning efficient water allocations and conservations measures. Therefore, in this paper we fit a time series model that best describes rainfall patterns of Kakamega county for the general ARIMA and generated the values of (P, D, Q) to forecast average expected monthly rainfall. Also we use R software for verification and data fitting of the model. The data we have used is from the Kakamega meteorological station in Kakamega.

Forecasting Inflation in Kenya Using ARIMA Model

2024-07-02T08:21:18+00:00

This study was to investigates the dynamics of inflation in Kenya through the application of advanced time series modeling techniques, specifically Autoregressive Integrated Moving Average (ARIMA) analysis. Inflation is a critical economic indicator that directly influences monetary policy, investment decisions, and overall economic stability. Given the dynamic of inflation in emerging economies such as Kenya, a fine understanding of its patterns and the ability to make accurate forecasts are imperative for policymakers, businesses, and investors. The ARIMA(2,2,2) model was employed to capture the underlying trend and seasonality in the inflation data, providing insights into the historical behavior of inflation in Kenya. In this study, we used R programming software and STATA to analyze and generate meaningful information from the data. The data was obtained from World Bank for a period from 1960 to 2022.

Statistical Analysis of the Effect of Educational Opportunities and Community Involvement on Adolescents and Sexual Reproductive Health Policy on Retention of Girl Child in Public Secondary Schools in Butula Sub-County, Kenya

2024-07-02T08:26:57+00:00

Girls’ retention in schools has been found to be a major challenge. Failure to retain girls in secondary schools can be considered as a waste of potential human resources and money spend on them in primary education and time lost in sending them to school in the first place. These girls may become a breed of illiterate women who are less productive economically, socially and politically. Among the critical contemporary social issues affecting many countries is teenage pregnancies. This research, therefore, analyses the effect of educational opportunities and community involvement on girl child retention in public secondary schools in Butula sub-county, Kenya using statistical method. Specifically, the research seeks to establish statistically the impact of educational opportunities and community involvement on girl child retention in public secondary schools in Butula Sub-county, Busia County. The study targeted a sample size of 300 respondents which were selected using convenient and purposive sampling techniques based Mugenda and Mugenda (2004) formula. Also, the data from both primary and secondary sources was used in the study. The instruments for gathering the data comprised questionnaires, interviews, and records from the schools. A SPSS version 25 was used to establish any link between the Adolescent Sexual Reproductive Health Policy and girl child retention in public secondary schools Butula Sub-County, Busia County. This study will increase understanding of the effect of teenage pregnancy on class attendance in public secondary schools in Butula Sub- county. The findings of the study indicated that girls missed school during their menstruation because sanitary facilities were inadequate.