The price of grains like maize and sorghum is subject to significant fluctuations, which can have a significant impact on a country's economy and food security. The aim of the study is to model sorghum and maize price volatility in Nigeria. The data utilized in the study was extracted from World Bank Commodity Price Data (WBCPD), 2022. The data consists of monthly prices in nominal US dollars for maize and sorghum from January 1960 – August 2022. The Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models were utilized for capturing the two-grain price volatility. Two types of conditional heteroscedastic models exist, the first group uses exact functions to control the evolution of , while the second group describes with stochastic equations. It is inferred from the result that inherent uncertainties and fluctuations existed in the prices of maize and sorghum in Nigeria which implies that the price volatility is positive and statistically significant suggesting that historical information and past shocks play a crucial role in determining the volatility observed in the grains. It is recommended that the ARCH, GARCH, EGARCH, TGARCH, PARCH, CGARCH, and IGARCH models should be employed for modeling and managing the volatility of maize and sorghum prices in Nigeria. These models have shown effectiveness in capturing different aspects of volatility, including the impact of past shocks, conditional volatility, asymmetry, and other relevant factors.

The Nigerian Government both previous and present has introduced several policies and programmes to reduce or proffer remedial measures to militate against the negative impact of high inflationary levels on the Nigerian economy. All these measures have not led to a productive result as the inflation rate has continued to sour higher over the years. This paper aimed at examining the economic influence of the determinant factors that influence inflationary trends that are multi-dimensional and dynamic which continue to defy solutions. The data used for this work was sourced from the National Bureau of Statistics and Central Bank of Nigeria, from 1983 to 2020. The ordinary least square approach was used to analyze the data and the result shows that consumer’s price index, interest rate and total export has a positive effect on Nigeria inflation, but only the Consumer’s Price Index (CPI) have a statistically significant effect on the Nigeria inflation at 99% confidence interval. Result also shows that the exchange rate, foreign reserve, money supply, real GDP, real income and total imports has a negative effect though not statistically significant on the Nigeria inflation rate. The result of the granger causality test shows exchange rate and total imports to granger cause Nigeria inflation. It is recommended that Government should improve locally manufacture products to meet international demands to reduce total imports.