摘要：The copper price in copper mining companies is an essential aspect in terms of profit, revenue, production targets, and hedging. This research aims to determine an alternative of copper price modeling and its causality relationship to Freeport McMoRan (FCX) stock price. The methods utilized in this research were Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN), Genetic Algorithms (GA) and Granger Causality Test. Based on this research result, all modeling methods equally show excellent performance for modeling copper price. Another finding from this research is that the copper price positively affects the FCX stock price. Therefore, it can be concluded that the copper commodity price influences the value of a copper mining company. The results of this research can be utilized as a reference for company analysts as a part to estimate profit probability, estimate revenue, estimate production targets, and hedging strategies. Keywords: ARIMA, causality, genetic algorithm, neural network, price model
