David Oluseun Olayungbo

By David Oluseun Olayungbo

This study applies Bayesian graphical networks (BGN) using Bayesian graphical vector autoregressive (BGVAR) model with efficient Markov chain Monte Carlo (MCMC) Metropolis-Hastings (M-H) sampling algorithm in a dynamic interaction among monetary policies and macroeconomic performances in Nigeria for the period of 1986Q1–2017Q4. The motivation stems from the instability in the movement of exchange rate, inflation rate and interest rate in Nigeria over the past years as a result of the structure of the economy. In this way, the monetary authority periodically applies the various policy instruments to stabilize the economy using reserve and money supply as at when due. This study adapts VAR and SVAR structure to examine the dynamic interaction among variables of interest, using BN, to provide a better understanding of the monetary policy dynamics and fit the changing structure of the Nigeria’s economy as regards the dynamics in her economic structure. Our results show that inflation is the strong predictor of interest rate in Nigeria. A monetary policy of broad inflation targeting is recommended for the country.

Part of the book: Bayesian Networks

By David Oluseun Olayungbo

This present study examines the volatility effects of the oil price on the stock price returns in Nigeria from the period of 2000M(12) to 2020M(4) on a monthly data using both standard GARCH and non-linear GARCH models. The motivation for the present study is the recent fall in the global oil price of Brent Crude to US$15.25 per barrel due to the outbreak of the Corona Virus (COVID-19). Consequentially, the Nigerian stock market (NSE) responded with a fall of 4172 point or by a fall of 15.53%. After establishing the presence of heteroscedasticity through the ARCH test and volatility clustering through the returns, the outcome of the study contributes to knowledge by providing financial information and signals to investors about the best GARCH model response to proactively and successfully use to model global oil price shocks so as to reduce financial risk in Nigeria’s stock market.

Part of the book: Linear and Non-Linear Financial Econometrics

By Kehinde Mary Bello, David Oluseun Olayungbo and Benjamin Ayodele Folorunso

The study examined the asymmetric relationship between exchange rate volatility and macroeconomic performance in Nigeria covering the period between 1986Q1 and 2019Q4. The Non-linear Generalised Autoregressive Distributive Conditional Heteroscedasticity (GARCH) model was employed. The study was motivated as a result of periodic increase in exchange rate of naira to a dollar and instability of macroeconomic variables in the economy. The presence of Autoregressive Distributive Conditional Heteroscedasticity (ARCH) effect established the use of non-linear GARCH models which showed that volatility was persistent over the period of study. Consequently, the result revealed that exchange rate volatility exhibited a positive relationship with trade balance, industrial output and inflation in the study period. Thus, good news prevailed more over bad news in the foreign exchange market. The study therefore recommended that monetary authorities in Nigeria should regulate exchange rate and macroeconomic variables in order to control the general price level in the economy.

Part of the book: Macroeconomic Analysis for Economic Growth