Contemporaneously, Value at Risk (VaR) is one of the most important measures of risk which is percentile of the profit and loss distribution of a portfolio over a specified period. We could explore portfolio risk and loss created through quick movement of the economy by using dynamic VaR method. To analyze VaR of the Jan.2006 to Sep. 2014 corn and soybean spot prices in CBOT, we propose the application of stochastic volatility with Student-t errors (SV-t) model that maximizes expected returns subject to a Value-at-Risk constraint to depict the risk of heteroscedasticity and leptokurtic accuracy. We also propose the efficient and best way-- Markov Chain Monte Carlo (MCMC) simulation estimation method. Empirical results show all coefficient estimates including jump effect and leverage effect, and that the VaR value of soybean is larger than that of corn indicating more price volatility in soybean than corn with shocks in the emerging international commodity markets. Speculators as well as business operators might be able to earn risk premium or avoid risk loss by the operation of portfolio changes. However, both corn and soybean price VaR value are more than 5% indicating possible underestimates of returns from portfolio operations. It is suggested that more portfolio returns of soybean and corn futures market operation may be available.