Abstract
Using data from the Dalian Commodity Exchange from January 2010 to December 2019 as a training set, this study develops an optimal seasonal autoregressive integrated moving average model (SARIMA) in Python to predict the settlement price of corn futures. Further, the model’s forecast accuracy and applicability are tested by predicting the price of corn futures from January 2020 to December 2020 and comparing it with the actual settlement price of active corn futures contracts in 2020 after the outbreak of COVID-19. The results show that the SARIMA (2,1,0) (3,1,1)12 model can accurately predict the settlement price. Moreover, COVID-19 had a positive short-term impact on the settlement prices.
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