DOES MACRO ECONOMIC VARIABLES HAVE EFFECT ON STOCK MARKET MOVEMENT IN NIGERIA?

Over the past decades, numerous studies have analyzed the relationship and the different results obtained from these studies have motivated further research. The relationship between Average share price and macro – economic variable has been well documented for the developed markets. However, this paper seeks to address the question of whether macro – economic variables have a significant with stock market movement using time series annual data for the period from 1985 – 2008. The selected macro – economic variables for study include external debt, inflation rate, real interest rate, investment, and exchange rate. The research entails the use of Argumented Dickey Fuller test, multivariate cointegration test, vector error correction, variance decomposition and causality analysis. The result was that all the variables were stationary at 2nd difference, four cointegrating equations were present i.e. long run relationship exists between the selected macro –economic variable and average share price. All macro – economic variables were insignificant but all negative relationship with ASP but only External debt was significant related to ASP. ASP and External debt were found to granger cause in pairs while an independent causality exists between the selected macro – economic variable and ASP. These show that ASP is not a leading indicator for the selected macro – economic variable. Keywords: Macro-economic, Stock market, Inflation rate, multivariate cointegration test, External deb

Count Models Analysis of Factors Associated with Road Accidents in Nigeria

The current state of all Nigerian roads is in poor condition, and reports of accidents have been recorded across the federation. The larger mission of the sustainable development goal is to promote sustainable cities and communities. This research study aims to examine factors responsible for road accidents in Nigeria through the quantitative tool of higher extensions of the Poisson regression model (ZTNPRM). A cross-sectional study design was adopted and secondary data was used within a sample period from the 1st quarter of 2006 to the 2nd quarter of 2020. Due to overdispersion, ZTNPRM indicates human errors contribute to a large proportion (41.4%) of road accidents. Vehicle factors are also statistically and positively related to road accidents. All the factors this model identified that lead to road accidents predicted low road accidents. Hence, the study recommends that Nigerian car users follow all rules and regulations associated with safe driving and make the environment safer for people as the sustainable development goal (SDGs). This study recommends more attention to the area of accident and injury prevention as a strategic objective of the SDGs

Bayesian Spatial Analysis of Socio-Demographic Factors Influencing Smoking, Use of Hard Drugs and Its Residual Geographic Variation among Teenagers of Reproductive Age in Nigeria

The use of hard drugs (Alcohol, cocaine and Nicotine) has remained the censorious issue globally and in Nigeria. The use of hard drugs and tobacco smoking is common in the stage of adolescence and youth life, which is a deterrent to education and career advancement. Hence, this study looks into socio-demographic factors that influence the use of hard drugs and tobacco smoking among teenagers between the ages of 15 years to 19 years. To achieve this objective, a cross-sectional data was used and a secondary data was obtained from DHS - National Demographic and Health Surveys (NDHS) from the survey year 2018. Some Bayesian models were developed and Conditional Autoregressive (CAR) model with random walk 1 (RW1) was the best model. The study unveiled a positive significant association of settlement, previous place of residence, education attainment, religion, ethnicity, literacy with reported use of hard drugs amongst teenagers of reproductive age

Measure of Volatility and Its Forecasting: Evidence from Naira / Dollar Exchange Rate

In the last five decades, Box Jenkins methodology has been in existence to model univariate time series data but fails or has limitations on modeling volatility. Most financial time series data do exhibit heavy tail and thick distribution, to this effect various parametric and semi-parametric non –linear time series models have been proposed two or three decades ago to capture volatility. However, this research entails measuring volatility and its forecasting using time series exchange rate annual data over the period from 1981 to 2020 (wide periodicity). The exchange rate was transformed to return, and parametric non –linear time series was modeled on it. It was found out that GARCH (1,2) reveals continuous volatility for short while and was the best model to predict the exchange rate volatility based on the evidence from measurement volatility tool; RMSE, MAE, MAPE among other extensions of GARCH models; EGARCH and TGARCH. EGARCH (1, 4) captures the asymmetry effect revealing that negative shocks will persistently have an effect on the volatility of the naira/dollar exchange rate

Measure of Volatility and Its Forecasting: Evidence from Naira / Dollar Exchange Rate

In the last five decades, Box Jenkins methodology has been in existence to model univariate time series data but fails or has limitations on modeling volatility. Most financial time series data do exhibit heavy tail and thick distribution, to this effect various parametric and semi-parametric non –linear time series models have been proposed two or three decades ago to capture volatility. However, this research entails measuring volatility and its forecasting using time series exchange rate annual data over the period from 1981 to 2020 (wide periodicity). The exchange rate was transformed to return, and parametric non –linear time series was modeled on it. It was found out that GARCH (1,2) reveals continuous volatility for short while and was the best model to predict the exchange rate volatility based on the evidence from measurement volatility tool; RMSE, MAE, MAPE among other extensions of GARCH models; EGARCH and TGARCH. EGARCH (1, 4) captures the asymmetry effect revealing that negative shocks will persistently have an effect on the volatility of the naira/dollar exchange rate