In this paper, we use stock price data between the years 2007 and 2010 to investigate the allocation of assets on the GSE. The Classical Markowitz optimization method shows that, the most profitable portfolio is obtained by investing 90% of wealth in non-financial assets and 10% in financial assets. Risk aversive investor who goes for the minimum risk portfolio has to invest 80% in non-financial assets and 20% in financial assets. We also find that, if the investor decides to split his wealth among the financial and non-financial asset equally, his profit will not be as much as the minimum and the optimum risk portfolio. In effect, there is a reward for risk on the GSE but the Markowitz optimization strategy never exceeds the buy and hold strategy of the market index.
Background: Low birth weight refers to new borns weighting less than 2.5 kg at birth. In November 2017, the WHO reported a global prevalence of 15.5% with 96.5% of these cases happening in developing countries. Whilst this is a global canker, the risk factors differ from locality to locality. This study aims at determining which maternal factors explains low birth weight baby delivery in the Lower Manya Krobo Municipality.Methods: The chi-square test for independence was used to test for independence. The binary logistic model is fitted for the associated factors. The receiver operating characteristic (ROC) is used to classify unbiased estimators.Results: ANC (yes β= -2.769 sig.=0.000); Alcohol (none β=-1.479 sig.=0.000, occasionally β= −2.043 sig.=0.000); Age (<20years β=0.178 sig. =0.676, 20 to 25years β= -1.487 sig.=0.000, 26 to 30 β= -0.941 sig.=0.086); Education level (None β=2.778 sig. =0.000, primary β=3.090 sig.=0.000, JHS β=1.913 sig.=0.002, SHS/Secondary β=1.951 sig.=0.000); Exposure to Heat (Yes β=4.507 sig.=0.000). AUC education=0.67, 95% CI=0.6,0.7 and AUC Exposure to heat=0.73, 95% CI=0.68,0.77 of low birth weight.Conclusions: Social status was not significant factor. Mothers exposed to heat had the highest risk (odds=90 times). Adolescent mothers stand high risk with odds 1.195. Mothers who attended antenatal clinics were at 94% less likelihood. Mild drinkers had lesser risk compared to no and heavy drinkers. Mothers with primary education (odds=21 times) were the riskiest compared to mothers with tertiary education. This differs from researches where no education mothers were riskiest. Only mother’s exposure to heat was found to be fairly good unbiased estimators.
The cost of malaria treatment is crippling Ghana's health budget. Malaria slows down economic growth and if not checked, it can erode the National Health Insurance Fund (NHIF). The cost of treating malaria in 2008 was US $772.4 million. This amount is equal to Ghana's entire health budget for 2008, which represents 10% of the country's entire Gross Domestic Product for 2006 (MOH Report - Quashigah, 2008). The financial cost of malaria treatment and its cost mitigation in Ghana is determined using actuarial models and a health scheme which also mitigates the cost of malaria is postulated. The KNUST hospital is the case study for obtaining the treatment cost of malaria. This study involves estimates of morbidity and mortality rates for malaria. Furthermore, a premium formula is developed using the cost data obtained from the hospital and the premium formula. Premium rates are calculated for the different scheme members, based on some predetermined factors. Ultimately recommendations have been made about how this proposed scheme can be incorporated into the current National Health Insurance Scheme (NHIS)
This study shows how options can be used for hedging crude oil price risk in accordance with broad-based hedging strategies. Furthermore, it demonstrates how options are priced using the Black-Scholes model and the benefits of hedging via options. The potential losses and gains anticipated through hedging are illustrated using the scenario in the context of the current oil finds in commercial quantities in Ghana.
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