Abstract
In this contribution, we describe our investigation of using fuzzy and fractal technology for analysing time series of market data. For having a comparizon, we implemented the commonly accepted technical indicator method. Then, 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. In the sequel, 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 compared the results obtained and present some interesting results of our experiments.
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Kroha, P., Lauschke, M. (2012). Fuzzy and Fractal Technology in Market Analysis. In: Madani, K., Dourado Correia, A., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2010. Studies in Computational Intelligence, vol 399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27534-0_16
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DOI: https://doi.org/10.1007/978-3-642-27534-0_16
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