Stock Market Development, Foreign Direct Investment and Macroeconomic Stability: Evidence from Nigeria

Stock market development is not only important in economic development of a nation, it is also an important indicator of future economic activity and a nation’s economic strength. This paper employs the Johensen co-integration and the error correction mechanism (ECM) techniques to examine the impact of foreign direct investment and macroeconomic stability (exchange rate and inflation rate) on the level of development of the Nigerian stock market over the peiod 1981-2010. The results reveal that a long run relationship exists between the variables and FDI was found to have a positive but insignificant impact on stock market development. The results also demonstrate that inflation rate has a negative insignificant effect but exchange rate has a significant and negative relationship with stock market development. The paper recommends that foreign firms operating in the Nigeria’s oil and gas and telecommunication sectors should be encouraged to be listed to promote the development of the market. This should be complemeted with policies that will promote macroeconomic stability to attract more foreign direct investment and making the contribution of the foreign direct investment meaningful to the economy. Keywords: Stock market development, FDI, macroeconomic stability, error correction model, Nigeria

Investment Portfolio Optimization Model with Mean-Std Deviation

Stock investment is an investment in securities with the hope of getting profits in the future. Investors are expected to make a series of portfolios to get optimal results from investments. This discussion aims to find the weight of the funds invested along with the returns and risks. The method used is the mean + std deviation. The results of this portfolio optimization show that the risk aversion coefficient is 0.1. The optimum weight for investment in each company is KLBF (22.67%), PGAS (8.796%), BBCA (41.77%), ASII (8, 24%), and SMAR (18.52%) with a maximum ratio of 8.8% of a return of 0.0881% and a risk of 1.0009%. The results of this portfolio optimization are expected to help investors by dividing the number of funds to be invested by the return and risk

Personal Characteristics and Banking Behaviour of Customers: Further Evidence from Usmanu Danfodiyo University Sokoto-Nigeria

“This study examines the extent to which customers’ personal characteristics have influence on the banking bahaviour of customers. The study uses primary data which was collected from the Usmanu Danfodiyo University Sokoto. A sample of 383 respondents was used cutting across staff, students and petty business operators within the community. The study uses Logistic regression model to analyse the data. The results of the study indicated that age, marital status, and occupation have negative influence on the banking bahviour of customers while, educational qualification and monthly income have positive influence. The study therefore recommends that those factors with positive influence should be closely watched whenever banks are looking for customers in the community and other communities with similar features.

Conformable Fractional Differintegral Method For Solving Fractional Equations

The standard approaches to the problem of conformable fractional calculus has been studied extensively. Many researchers have shown that the obtained conditions for the theorem describing the general solution of; y a ( x ) y b ( x ) are generally weaker than those derived by using the classical norm-type expansion and compression theorem. In this paper, we propose conformable method for the fractional differential transform and established the prove for basic properties of differintegrals. Some solved examples have been reported to illustrate the possible application of the obtained results.The authors wish to thank A, B, C. This work was supported in part by a grant from XYZ

Generating nested XML documents from unnormalized relational views using a statistically approach

Converting relational database into XML is increasing daily for publishing and exchanging the business applications data on the Web. Most of the current approaches and products convert the unnormalized relational views to XML documents using flat-based that causes data redundancy which leads to generate a massive data. This paper proposes an approach to generate nested XML documents with full automatic from flat relational views. The proposed approach includes two steps: the first is extracting the nested view from the flat relational view using a statistically approach for counting and removing the data redundancy. The statistically approach is based on the analysis of functional dependency taking into account the frequency of the data values for the columns of the relational views. The second step is converting the nested view into nested XML. The columns of the nested view are also divided into groups to achieve the nesting for XML document. The proposed approach generates nested XML documents from the unnormalized relational views with full automatic. The generated nested XML document by the proposed approach has good features such as minimal redundancy and less size of storage

Generating free redundancy XML documents from non normalized relational views using a statistically approach

Converting relational database into XML is increasing daily for publishing and exchanging the business applications data on the Web. Most of the current approaches and products convert the non normalized relational views to XML documents using flat-based that causes data redundancy which leads to generate a massive data. This paper proposes an approach to reduce the redundancy for the XML documents that are generated from non normalized relational views. The proposed approach includes two steps: the first is extracting the nested view from the flat relational view using a statistically approach for counting and removing the data redundancy. The statistically approach is based on the analysis of functional dependency taking into account the frequency of the data values for the columns of the relational views. The document based on the blocks that are created according to frequency of the data values for the first column which has the most frequent of the data values

Forecasting Human Development Index With Double Exponential Smoothing Method And Acorrect Determination

Human development is now seen as a measure of the success of the development of a nation which is closely related to the economic, social, cultural, political and environmental fields. The success of human development is measured based on the Human Development Index (IPM). Boyolali Regency is one of the regencies in Central Java Province which has diverse and abundant natural resources. The large potential of natural resources owned should be in line with the quality of human development. However, it turns out that this is not in line with the HDI value of Boyolali Regency which is still below the average HDI value of Central Java. So that the Boyolali government continues to strive to maximize the potential and increase the HDI value. Based on this, it is necessary to do forecasting as a reference to maximize the level of human development in Boyolali Regency in the next few years. In this study, HDI forecasting in Boyolali Regency was carried out using the Double Exponential Smoothing method from Brown with the data used is HDI data in Boyolali Regency from 2011 to 2021. The data used was obtained from the Central Bureau of Statistics (BPS) Boyolali Regency. HDI forecasting was also carried out using the arithmetical method, and the best forecasting results were compared between the two methods based on the mean absolute percentage error (MAPE). Forecasting results using the Double Exponential Smoothing method produce the best alpha smoothing parameter values of 0.91 and MAPE values of 0.4061%. Meanwhile, using the arithmetic series method, the MAPE is 0.4704%. Both methods produce MAPE values with very good criteria, so that both methods can be used for forecasting. However, based on the criteria for the smallest MAPE value, the Double Exponential Smoothing method is used. The results of the HDI forecasting using the Double Exponential Smoothing method for 2022, 2023 and 2024 are 74.61, 74.81 and 75.02 respectively. While the results of forecasting with arithmetical method for the same years are 74.93, 75.45, and 75.98

Barzilai-Borwein gradient method for solving fuzzy nonlinear

In this paper, we employ a two-step gradient method for solving fuzzy nonlinear equations. This method is Jacobian free and only requires a line search for . The fuzzy coefficients are presented in parametric form. Numerical experiments on well-known benchmark problems have been presented to illustrate the efficiency of the proposed method