Aims: To model exchange rate values between Naira and US Dollar in order to assess the effect of the COVID-19 pandemic period on the rate by examining the forecasts. Study Design: The study design is the longitudinal research design. Place and Duration of Study: Real life data of monthly average Nigerian Naira-US Dollar exchange rates from Jan.1991 to April 2020 obtained from the Data and Statistics publication of Central Bank of Nigeria. Methodology: The traditional time series ARIMA model is employed for forecasting Naira/Dollar exchange rate using Monthly data covering the period January, 1991 to April, 2020. The ACF and PACF plots showed tendency that the differenced exchange rate data behave as both having autoregressive and moving average processes as the ACF has significant peaks at different lags and a gradual decay to zero is indicated by the PACF. Results: Using the AIC, BIC, and HQC as model selection criterion the ARIMA (2, 1, 3) were selected as the model with the best fit for the exchange rate data as compared to the other selected models. The ACF of the residuals is plotted with lags up to 20 and the residuals coefficient did not exceed the 95% confidence limit which indicates that the model is a good fit and is appropriate for the data. Plots of in-sample and out-of-sample forecast were also made. Conclusion: The out-of-sample forecast plot for period of 12 months revealed that naira will continue to depreciate on US dollar for the period forecasted with very high tendencies during the COVID-19 pandemic period.

The interest to carry out volatility analysis of crude oil production in Nigeria in this paper is motivated by the shortfalls in quantities of crude oil produced in recent past, given the country's high dependence on oil and its contribution to the nation's economic development. In 2016 precisely, the country experienced drastic instability in prices of crude oil at international markets and dwindling production quantities due to vandalism on oil facilities and other corrupt practices in the sector. This paper aims at using volatility measures to investigate variability of crude oil production as an assumed contributor to the economic downturn observed in the recent past in Nigeria. The data used are crude oil production data in millions of barrels collected from NNPC Statistical Bulletin. Variance of the crude oil series has been fitted with ARCH (2) model. ARCH (3) and GARCH (3,3) models are also fitted to the variance of the error obtained from ARIMA(0,1,1). ARCH and GARCH models have shown evidence of volatility in the series. The parameter estimate of the non-linear component of the bilinear model fitted to the crude oil data could not capture volatility clustering. This explains the superiority of ARCH and GARCH model over bilinear model when fitting volatile series. Synonymous with oil price volatility, evidence has it that crude oil production data are volatile. Although, Nigerian government's intervention and negotiations with Niger Delta Militants to end operational attacks on oil facilities yielded positive results, fact has been established that the two economic variables (production and price) are volatile, as contributors to the recent past economic recession in Nigeria. It is important for the stakeholders in the sector and Nigerian government to always exhibit proactive measures against illicit activities that negatively affect oil production at all times and ensure maximum control of crude oil production process and militating factors during price shocks to avoid uncontrollable economic instability.