http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/147 Thu, 29 Oct 2026 21:33:09 GMT 2026-10-29T21:33:09Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/32029 Title: ADAPTIVERANGE-BASEDVOLATILITY MODELLINGOF OIL AND GAS STOCK RETURNS IN NIGERIA Authors: Tanimu, Mohammed; Isah, Audu; Yakubu, Yisa; Adetutu, Olayiwola Matthew Abstract: In this article, a range based volatility model that integrated robust hybrid range-based estimators with exogenous variables was proposed for oil and gas sector. The study employed historical daily data on opening, closing, high, and low prices of stocks from Chevron, Conoil, Oando Plc, and Total Energies, spanning 1 January, 2012 to 12 September, 2025, alongside daily Brent crude oil prices as an exogenous variable. The model and exogenous influences on volatility was examined. The study showed that Range-Based Generalised Autoregressive Conditional Heteroskedasticity with Exogenous variable (RB-GARCH-X) models, especially the non-zero drift version, captured volatility in Nigeria’s oil and gas sector effectively, while the adaptive RB-GARCH-X model that adapt to both drift-free and drift-present conditions performed best for highly volatile stocks. The results also revealed that range-based estimation techniques improved model robustness against microstructure noise and estimation errors in both drift-free and drift-present conditions. Parameter estimates indicated strong volatility persistence (β: 0.71–0.99), moderate short-term effects (α: 0.03–0.21), and significant influence of crude oil prices (γ: ≈2.0E-07 to -1.25E-07). The adaptive model provided a more effective balance between short- and long-term effects, demonstrating its robustness for stocks characterised by heightened instability like the Nigeria Oil and Gas stock. Description: The study developed a range-based volatility model incorporating robust hybrid estimators and crude oil prices as an exogenous variable to analyse stock market volatility in Nigeria’s oil and gas sector from 2012 to 2025. The analysis covered Chevron, Conoil, Oando Plc, and TotalEnergies, using daily opening, closing, high, and low stock prices alongside Brent crude oil prices. The results showed that the Range-Based GARCH-X model, particularly its adaptive version, effectively captured volatility and performed well under both drift-free and non-zero drift conditions. The findings revealed strong volatility persistence, moderate short-term effects, and a significant influence of crude oil prices on stock volatility. The study concluded that the adaptive RB-GARCH-X model provides a robust and reliable approach for volatility estimation and risk management in Nigeria’s oil and gas stock market. Sat, 09 Aug 2025 00:00:00 GMT http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/32029 2025-08-09T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/32028 Title: On Retention and Growth Patterns of Abuja Electricity Distribution Company Metered Customers through Times Series Forecasting. Authors: ADETUTU, OLAYIWOLA MATTHEW Abstract: This study investigates the long term growth dynamics of metered customers within the Abuja Electricity Distribution Company (AEDC) from 2015 to the first quarter of 2024, using descriptive analytics, trend modelling, and time series forecasting. The descriptive analysis shows a sustained upward trajectory in metering coverage, characterized by policy driven surges during key roll out periods. A linear trend model reveals a highly significant positive slope β = 4, 946.69 and strong explanatory power (R2 = 0.94), confirming that time is a dominant driver of metering expansion. Annual retention rates further highlight substantial growth in several years, with values exceeding 110% during intensive metering campaigns. In order to forecast future metering performance, multiple ARIMA models were compared, and ARIMA (1, 1, 1) emerged as the optimal specification based on lowest AIC, BIC, RMSE, and MAPE values. The model’s Ljung-Box p-value of 1 indicates that residual autocorrelation is fully addressed which validate its suitability for forecasting. Projections for 2024–2028 indicate continued growth under current operational and policy conditions. Overall, the findings demonstrate strong historical progress and provide a statistically sound basis for future planning and metering investment strategies within AEDC. Description: he study examines the retention and growth patterns of metered customers of the Abuja Electricity Distribution Company (AEDC) from 2015 to the first quarter of 2024 using descriptive statistics, trend analysis, and time series forecasting. The results reveal a sustained increase in metered customers, with the linear trend model showing a significant positive growth rate of 4,946.69 customers per time period and a strong explanatory power of 94%. Among the ARIMA models evaluated, ARIMA (1,1,1) was identified as the most suitable forecasting model based on its information criteria and prediction error measures. The model projects continued growth in metered customers from 2024 to 2028, while its Ljung–Box test result indicates no evidence of residual autocorrelation. The study concludes that the findings provide a reliable statistical foundation for AEDC's future metering investment, operational planning, and electricity service expansion strategies. Wed, 18 Mar 2026 00:00:00 GMT http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/32028 2026-03-18T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/12876 Title: A STUDY OF THE EFFECTS OF BAKING MATERIALS AND OVEN TEMPERATURE ON CAKE HEIGHT: SPLIT-PLOT CENTRAL COMPOSITE DESIGN APPROACH Authors: Yakubu, Yisa; Aliyu, ZQ; Usman, A; Evans, PO Abstract: Most people love a delicious piece of cake. But what is the secret to a good cake? While many may comment on flavor, frostings or other attributes, most people agree on one thing: texture. The texture of the cake needs to be “fluffy”. While there are exceptions to the traditional textures, one of the easiest ways to get the right texture of a cake is by having the cake rise to a maximum height. By having the tallest cake with the same amount of starting material, more air is allowed into the cake, thereby creating the “fluffy” texture that people desire. In this work, a central composite design (CCD) experiment within a split-plot structure was conducted to assess the impact of some baking materials on cake height. The experimental factors (cake-baking materials) include oven temperature (factor A), amount of flour (factor B), baking powder (factor C), and amount of milk (factor D) with a fixed amount of other necessary ingredients present. The generated data were analyzed using Design Expert (version 10) statistical package. The restricted maximum likelihood (REML) estimates of the variance components were first obtained and the generalized least squares (GLS) estimator was used to obtain the factor effects estimates. The set of levels of these factors that yields optimum value of the cake height (the stationary point) was then sought using optimization facility of the statistical package. It was observed that each of the linear terms: A, B, C, D, the interaction term: BC and the quadratic terms: A2 , C2 , and D2 contributes significantly to the height of the cake. The fitted generalized least squares model accounted for 95% of the total variation in the cake height. The estimated optimum cake height was found to be 𝑦̂ = 11.047 at the stationary point: 𝑜𝑣𝑒𝑛 𝑡𝑒𝑚𝑝 = 250𝑜𝐶, 𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑓 𝑓𝑙𝑜𝑢𝑟 = 1.5 𝑐𝑢𝑝𝑠, 𝑏𝑎𝑘𝑖𝑛𝑔 𝑝𝑜𝑤𝑑𝑒𝑟 = 1.5 𝑡𝑒𝑎𝑠𝑝𝑜𝑜𝑛𝑓𝑢𝑙𝑙, 𝑎𝑛𝑑 𝑚𝑖𝑙𝑘 = 0.75𝑐𝑢𝑝. Sun, 01 Jan 2017 00:00:00 GMT http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/12876 2017-01-01T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/9107 Title: Applied Regression Analysis(322): Multicollinearity Diagnoses And Solutions Using Ms-Excel Analysis toolpak Add-in Authors: Bello, Adeshina Oyedele Mon, 01 May 2017 00:00:00 GMT http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/9107 2017-05-01T00:00:00Z