Hurst Exponent and Trading Signals Derived from Market Time Series

Petr Kroha, Miroslav Škoula

2018

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.

Paper Citation

in Harvard Style

Kroha P. and Škoula M. (2018). Hurst Exponent and Trading Signals Derived from Market Time Series.In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-298-1, pages 371-378. DOI: 10.5220/0006667003710378

in Bibtex Style

@conference{iceis18,
author={Petr Kroha and Miroslav Škoula},
title={Hurst Exponent and Trading Signals Derived from Market Time Series},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2018},
pages={371-378},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006667003710378},
isbn={978-989-758-298-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Hurst Exponent and Trading Signals Derived from Market Time Series
SN - 978-989-758-298-1
AU - Kroha P.
AU - Škoula M.
PY - 2018
SP - 371
EP - 378
DO - 10.5220/0006667003710378