Abstract
The goal of the paper is to present an original concept of representation of financial high frequency data using Ordered Fuzzy Numbers. This approach allows the transition from high frequency data (e.g. ticks, minutes) to lower frequency data (e.g. daily) while maintaining more information about price movement at assumed time interval than using the popular price charts (e.g. Japanese Candlestick chart). The financial data are modeled using Ordered Fuzzy Numbers called further by Ordered Fuzzy Candlesticks. The use of them allows also modeling uncertainty associated with financial data. How to construct and use Ordered Fuzzy Candlesticks are presented in the main part of this paper.
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Marszałek, A., Burczyński, T. (2013). Modelling Financial High Frequency Data Using Ordered Fuzzy Numbers. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38658-9_31
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DOI: https://doi.org/10.1007/978-3-642-38658-9_31
Publisher Name: Springer, Berlin, Heidelberg
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