In this work we compare the performance of some
standard technical indicators with an interval technical
indicator, the moving interval (MI), for time
series forecasting. MI has the advantage of taking
into account the variability of data in the range
considered and not only the average, like standard
indicators do. However, the use of intervals as input
variables require the use of regression methods
able to handle with non Euclidean structures. The
kernel approach is employed to this end. A recently
introduced interval kernel is applied together with
the moving interval indicator. The conclusion is
that this indicator outperforms the forecasting performance
of standard indicators.
CitacióRuiz, F. [et al.]. An interval technical indicator for financial time series forecasting. A: International Workshop on Qualitative Reasoning. "25th International Workshop on Qualitative Reasoning : QR2011". Barcelona: 2011, p. 60-65.