haika mbwambo

Purpose: The fluctuation in the price of crude oil on the global market has created a lot of attention to the researchers to investigate its price movement. This study tries to address the problem of predicting crude oil prices in a situation of unusual circumstances. Methodology: In this study, Box Jenkins methodology was used to analyze monthly dynamics of the Brent oil price from January 2002 to February 2022. Data were first differenced to achieve stationarity, and then ACF and residual diagnostics were utilized to choose models that were used for analysis Findings: The performance of various models were evaluated and ARIMA (0, 1, 1) was found to be the best model for forecasting crude oil prices. This study further reveals that despite the corona virus and the Ukraine war having a considerable impact on crude oil prices, such a model is still capable of capturing the underlying volatility in crude oil prices. Originality/Value: Oil demand suddenly decreased as a result of the c...

This study aimed to examine the effects of COVID 19 pandemic on the liquidity and profitability of the Tanzanian banks that are listed in the Dar es  Salaam Stock Exchange. The study realised the objective by comparing the profitability and liquidity trend before and after the emergence of  COVID-19. The differences between these values were then statistically examined to evaluate the impact of COVID 19 on the trends before and after  the outbreak. The secondary data on the six selected banks were derived from the audited financial accounts for the six-year period (2016 to 2021),  which included the three years prior to and three years after the COVID 19 outbreak. The results showed that liquidity positions of most banks had  deteriorated. Regarding profitability, the results indicate that small sized banks experienced more declining profitability than was the case with big  banks. Furthermore, the statistical difference between the means of liquidity (proxy by liquidity ratio) and ...

The study looked at bank and industry-specific factors that influence listed commercial banks’ lending behaviour in Tanzania for the five-year period  from 2016 to 2020. Asset quality, capital adequacy, liquidity, and bank size were employed as bank-specific factors, whereas Gross Domestic Product  and inflation rate were used as industry-specific factors. To establish the cause and effect relationship between the response and  explanatory variables, the study used an explanatory research design. Secondary data were extracted from seven listed commercial banks’ audited  financial statements for a five year period, totalling 35 data points. After performing pre-regression analysis (multicollinearity test), correlation and  linear analysis were conducted. From 2016 to 2020, the study discovered that capital adequacy and bank size have the biggest impact on Tanzanian  listed commercial banks’ lending behaviour. At 5 per cent level, other explanatory variables such as asset quality, liq...

This study aims to examine the influence of bank-specific factors namely taxation, asset tangibility, profitability, and bank size on listed banks capital structure in Tanzania from 2016 to 2020. The study used an explanatory research design to determine the cause and effect relationship between the response variable and the four explanatory variables of Tanzanian listed banks. The study's population included all of the DSE's listed banks, with the researcher sampling seven of them. The test of multiple linear regression was carried out and findings revealed the capital structure of listed banks in Tanzania are affected by asset tangibility and tax as these two explanatory variables were significant at 5% level. However, the study reveals that profitability and bank size has no statistically significant impact on the capital structure of listed banks in Tanzania. This study is limited to seven listed banks at the Dar es Salaam Stock of Exchange (DSE) over a five-year period ...