The paper investigates the best fit estimation technique for modeling returns and volatility of corn. It further estimates the pass-through effects of volatility risks to corn returns. It provides two main innovations: first, it analyzes corn returns volatility types namely idiosyncratic and systematic volatility types using the Narayan and Popp (2010) test and further modified the estimations to include both symmetric and asymmetric volatility models. Second, it uses the Kalman filtering process to estimate the pass-through effects of volatility risks to returns of corn. The paper finds two structural breaks that occur in 2015/2016 and 2018. It notices the existence of persistence and leverage effects in the returns volatility of corn and that rising volatility regardless of types, necessitates demand for higher returns by investors to hold corn investment. Conclusively, it recommends that, when modeling corn return volatility, issues of asymmetric effects and structural shifts are extremely pertinent and that investors should structure investment portfolio with more of idiosyncratic volatility corn prices to maintain stable returns.
