Authors:
Petr Kroha
and
Miroslav Škoula
Affiliation:
Czech Technical University and Faculty of Information Technology, Czech Republic
Keyword(s):
Time Series, Trading Signals, Fractal Dimension, Hurst Exponent, Technical Analysis Indicators, Decision Support, Trading, Investment.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Group Decision Support Systems
;
Strategic Decision Support Systems
Abstract:
In this contribution, we investigate whether it is possible to use chaotic properties of time series in forecasting. Time series of market data have components of white noise without any trend, and they have components of brown noise containing trends. We constructed a new technical indicator MH (Moving Hurst) based on Hurst exponent that describes chaotic properties of time series. Further, we stated and proved a hypothesis that this indicator can bring more profit than the very well known indicator MACD (Moving Averages Convergence Divergence) that is based on moving averages of time series values. In our experiments, we tested and evaluated our proposal using hypothesis testing. We argue that Hurst exponent can be used as an indicator of technical analysis under considerations discussed in our paper.