INFFC data analysis: lower bounds and testbed design recommendations

The article summarizes the results of an exploratory data analysis on the INFFC competition time series. The analysis provides evidence that the problem is non-stationary and that the interpolation process for filling-in missing values alters the data distribution. The accuracy for trivial and linear predictors, determined in order to establish accuracy lower bounds for reasonable nonlinear prediction systems, identifies competition entries with prediction accuracies below the provided bounds. Finally, testbed design recommendations for future financial time series competitions are extracted from the results of this analysis.