Abstract

This paper introduces a model for intraday copper futures prices based on a stochastic differential equation (SDE). In particular, we derive an SDE that fits the model to the data and that is based on the whitening filter approach, a method characterizing linear time-variant systems. This method is applied to construct a model able to simulate the trajectories of copper futures prices, statistically described by means of an empirical autocorrelation approach. We show that the predictability of copper futures prices is rather weak. In fact, the developed model produces trajectories close to the actual data only in the short term. Consequently, the investment risk for copper futures is high. We also show that the performance of the model improves significantly if the time series satisfy particular conditions, e.g., those with a determinism measure.

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