USING FUZZY AND FRACTAL METHODS FOR ANALYZING MARKET TIME SERIES

P. Kroha, M. Lauschke

Abstract

In this contribution, we investigate the possibilities of using fuzzy and fractal methods for analyzing time series of market data. First, we implemented and tested a fuzzy component that provides fuzzyfication by the Mamdani Larsen inference method with static rules using not only Gauss but also Cauchy and Mandelbrot distribution. Second, we implemented and tested a fractal component that provides fuzzy clustering by the Takagi Sugeno method with dynamic fuzzy rules. Looking for an optimum, we simulated many parameter combinations and compared the results. We present some interesting results of our experiments.

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Paper Citation


in Harvard Style

Kroha P. and Lauschke M. (2010). USING FUZZY AND FRACTAL METHODS FOR ANALYZING MARKET TIME SERIES . In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICFC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 85-92. DOI: 10.5220/0003075200850092


in Bibtex Style

@conference{icfc10,
author={P. Kroha and M. Lauschke},
title={USING FUZZY AND FRACTAL METHODS FOR ANALYZING MARKET TIME SERIES},
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICFC, (IJCCI 2010)},
year={2010},
pages={85-92},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003075200850092},
isbn={978-989-8425-32-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICFC, (IJCCI 2010)
TI - USING FUZZY AND FRACTAL METHODS FOR ANALYZING MARKET TIME SERIES
SN - 978-989-8425-32-4
AU - Kroha P.
AU - Lauschke M.
PY - 2010
SP - 85
EP - 92
DO - 10.5220/0003075200850092