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Results 12771-12780 of 29393 (Search time: 0.012 seconds).
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Issue DateTitleAuthor(s)
2013-05Partial replacement of sand with sawdust in concrete productionAbdullahi, Aliyu; Abubakar, M.; Afolayan, A.
2013-05-30Towards the Adoption of Green Computing Techniques in Nigerian IT IndustriesUmar, Buhari Ugbede; Olaniyi, Olayemi Mikail; Ahmed, Aliyu; Salami, A. F
2011-09-11Nutritional and sensory properties of complementary foods prepared from sorghum, pigeon pea and mango flour blendsChinma, C E; James, S; Jegede, O A; YAKUBU, C M; Oloyede, O O
2011-10-10Effects of different processing methods on the proximate composition of guna flour.James, S; YAKUBU, C M; Baba, I A; Yusuf, J; Salaudeen, S T
2012-08-05Functional and Pasting Properties of Cassava Flour proceed with red Palm oil.Abu, J O; Ayangealumun, I; Chinma, C E; YAKUBU, C M
2021-10-28Trades in stock market anywhere in the world is faced with intense volatility due to stocks prices instability in real time that is mostly driven by information and other market dynamics. This research examines two volatility models with two different error distributions innovations in modelling and forecasting the continuous compounded return series (CCRS) of Nigeria All Share Index (NGX ASI) spot prices spanning the period of January 30, 2012 to June 30, 2021. The Generalized Autoregressive Conditional Heteroscedastic (GARCH) and Asymmetric Power Autoregressive Conditional Heteroscedastic ARCH (APARCH) volatility models under Student-t Distribution (StD) and Generalized Error Distribution (GED) error innovations are utilized. The best-fitted model is determined using Akaike’s Information Criterion (AIC) while Mean Square Error (MSE) is used to evaluate forecasts performance of the fitted volatility models. The results from the analysis showed that amongst competing models, APARCH (1,1)-GED was selected to be the best fitted volatility model with better forecasting power for the CCRS-NGX-ASI spot prices. This is because it produces the smallest AIC and MSE valuesGana, Y; Usman, A
2021Non-parametric decomposition of total factor productivity growth in yam production in North-Central NigeriaIsonguyo, R. G.; Ojo, M. A.; Jirgi, A. J.; Yisa, E. S.
2020-06-19Net Returns Maximizing Combination of Arable Crops among Smallholder Farmers in Kaiama Agricultural Zone of Kwara State, NigeriaAdewumi, A.; Tanko, L.; Ibrahim, F. D.; Yisa, E. S.
2020-04-20Analysis of Productivity of Rice Farmers in North-Central Nigeria.Isonguyo, R.G.; Ojo, M. A.; Jirgi, A.J.; Yisa, E. S.
2021-10-25Multivariate Analysis of Dynamic Transmission of Coronavirus Disease with Control Measures in Nigeria.Sheshi, M.M; Usman, A

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