Browsing by Author "Banjoko, Alabi Waheed"

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    Factor Influencing Changes in the Nigerian Equity Market at Different Forecast Horizons
    (Al-Hikmah Journal of Pure & Applied sciences, 2015) Garba, Mohammed Kabir; Afolayan, Razaq Bayo; Banjoko, Alabi Waheed; Salihu, F
    This study investigates the impact of macroeconomic variables on All Share Index (ASI) of the Nigerian Stock Exchange (NSE) and its contribution to equity market fluctuations at different forecast horizons. The study utilizes the Vector Error Correction Model (VECM), Granger Causality test, Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD) in estimating quarterly data from 2000 to 2014 extracted from Statistical Bulletin of the Central Bank of Nigeria (CBN). The results revealed that macroeconomic indicators are inefficient to explain the equity market in the short run while ASI shows responsiveness to the indicators in the long run. It was also discovered that ASI benefits from high exchange rates while inflation rate has an adverse negative effect and particularly serve as a major hindrance to business growth in Nigeria. Findings from this study have implications for policy makers, investors, researchers and stock market regulators on ways to achieve economic development sustainability in the long run via the use of financial indicators as important factors in explaining equity market movement
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    On Seemingly Unrelated Regression and Single Equation Estimators under Heteroscedastic Error and Non-Gaussian Responses.
    (FUOYE Journal of Engineering and Technology, 2020) Afolayan, Razaq Bayo; Banjoko, Alabi Waheed; Garba, Mohammed Kabir; Yahya, Waheed Babatunde
    - This study investigated the efficiency of Seemingly Unrelated Regression (SUR) estimator of Feasible Generalized Least Square(FGLS) compared to robust MM-BISQ, M-Huber, and Ordinary Least Squares (OLS) estimators when the variances of the error terms are non-constant and the distribution of the response variables is not Gaussian. The finite properties and relative performance of these other estimators to OLS were examined under four forms of heteroscedasticity of the error terms, levels of Contemporaneous Correlation (Cc) with gamma responses. The efficiency of four estimation techniques for the SUR model was examined using the Root Mean Square Error (RMSE) criterion to determine the best estimator(s) under different conditions at various sample sizes. The simulation results revealed that the SUR estimator (FGLS) showed superior performance in the small sample situations when the contemporaneous correlation (ρ) is almost perfect (ρ=0.95) with the gamma response model while MM-BISQ was the best under low contemporaneous correlation. The relative efficiencies of MM-BISQ, M-Huber and FGLS estimators over the OLS are respectively 89%, 71%, and 14% in a small sample (𝑛 ≤ 30) and 49%, 32% and 1% in large sample sizes (𝑛 > 30) under gamma response model. The study concluded that MM-BISQ and M-Huber estimators are the most efficient estimators for modeling systems of simultaneous equations with non-Gaussian responses under either homoscedastic or multiplicative heteroscedastic error terms irrespective of the sample size.
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    On the use of Linear Programming Model Approach in Profit Optimization of a Product Mix Company
    (Islamic University Multidisciplinary Journal (IUMJ), Uganda, 2020-04-25) Garba, Mohammed Kabir; Banjoko, Alabi Waheed; Yahya, Waheed Babatunde; Gatta, Nusirat Funmilayo
    This study employed the utilization of a slack starting solution approach of the Simplex Optimization method to build a Linear Programming (LP) model. Data were extracted from the record unit for an item blend fabricating industry, Fortunate Bakery, Ilorin, Nigeria. The information was collected on four noteworthy sorts of bread produced by the bakery which includes; Special Delight (SD), Ordinary Slice Bread (OSB), Ordinary Gala (OG) and Saloon (S) regarding their unit costs and selling prices, the raw materials utilized and the amount of each of the crude materials held in stock every day. In view of the data supplied, a linear programming problem was developed with the goal of maximizing the daily profit of the organization. The optimal daily profit that would be achievable to the organization in the item blend was resolved utilizing the methodology specified earlier. The results showed that the organization would achieve ideal daily profit level of ₦ 9,500 (or monthly profit level of ₦285,000) if she concentrates on the production of type alone is given to the unit offers of Saloon bread and disregard other lines of items produced by the company. By this, aggregate daily offers of about 380 (or monthly offers of about 11,400) units of Saloon bread would be sold by the organization. The data analyses were carried out USING Tora software package.