This research article aimed at modeling the variations in the dollar/cedi exchange rate. It examines the applicability of a range of ARCH/GARCH specifications for modeling volatility of the series. The variants considered include the ARMA, GARCH, IGARCH, EGARCH and M-GARCH specifications. The results show that the series was non stationary which resulted from the presence of a unit root in it. The ARMA (1, 1) was found to be the most suitable model for the conditional mean. From the Box–Ljung test statistics x-squared of 1476.338 with p value 0.00217 for squared returns and 16.918 with 0.0153 p values for squared residuals, the null hypothesis of no ARCH effect was rejected at 5% significance level indicating the presence of an ARCH effect in the series. ARMA (1, 1) + GARCH (1, 1) which has all parameters significant was found to be the most suitable model for the conditional mean with conditional variance, thus showing adequacy in describing the conditional mean with variance of the return series at 5% significant level. A 24 months forecast for the mean actual exchange rates and mean returns from January, 2013 to December, 2014 made also showed that the fitted model is appropriate for the data and a depreciating trend of the cedi against the dollar for forecasted period respectively.
The primary aim for this paper is to examine the pattern of rainfall in the western region of Ghana. Data was obtained from the Ghana Meteorological Agency. The sample include January to September pattern of the amount of rainfall, for the years 2006 to 2016. That is nominal daily rainfall recorded (1485) aggregated into monthly rainfall value (99 data point). The analysis includes fitting an auto regression moving average model (ARMA) model for the data. The series was found to be non-stationary which resulted from the presence of a unit root in it. The series became stationary after eliminating the unit root by finding the first difference in the amount of rainfall. The time series component found in the model were a trend and random variation. ARMA (1, 1) which has all parameters significant was fitted for the data and found to be the most suitable model for the conditional mean. A Ljung Box test statistic of 47.207 with a normalised BIC of 6.420 and a Root Mean Square error of 24.16 supported by a probability value of 0.001 show that the fitted model is appropriate for the data. An = 0.532 indicates that about 53% of the variations seen in the pattern of rainfall recorded for the period is being explained by the fitted model. The 18-month forecast for the mean actual rainfall and mean returns could show that the fitted model is appropriate for the data and an increasing trend of rainfall for the forecasted period.
Aims: As a result of the novel coronavirus (COVID-19) pandemic, the traditional face-to-face learning approach at tertiary institutions was replaced by an online learning model. This has a significant impact on tertiary students, teachers, and administrators, particularly in Ghana, where online learning has not been widely used in the past. The current study looked at how students' perceptions of the quality of their online learning experiences affected their acceptance of the paradigm before and after the COVID-19 prevalence. Study Design: The study adds to the body of knowledge by assessing how well the modified DeLone and McLean information systems success model applies to online learning. Place and Duration of Study: Technical Universities in Ghana between September 2021 and May 2022. Methodology: Structured questionnaires were used to obtain primary data from 1386 students at Ghana's technical universities. The study employed the multiple linear regression model to examine the effects of class and gender on students' opinions of the quality and preferences for the online learning model. Results: The study's findings revealed that the online learning system provided quality service to students, with a mean response value (MRV) ranging from 3.74 to 4.52. It was also discovered that 72% of students preferred online learning because of the system quality, information quality, and service quality provided. Conclusion: Students must be encouraged to pursue online education that is appropriate, cutting-edge, and useful if they are to succeed and remain relevant in the digital age. Tertiary institution administrators are being encouraged to improve the quality of the online learning environment for both students and teachers.
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