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Financial Stock Data and Ordered Fuzzy Numbers

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Artificial Intelligence and Soft Computing (ICAISC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7894))

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Abstract

Financial stock time series are presented together with the so-called Japanese candlesticks. Model of Ordered Fuzzy Numbers is shortly presented and its use in presentation of Japanese candlesticks. Then the ogive, the graphical representation of the cumulative relative frequency of transactions is introduced, as the next characteristic of price time series. Linear operations on ogive curves are defined. It is shown that ogive is reflecting some properties of stock time series additional to the Japanese candlestick.

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Author information

Authors and Affiliations

  1. University of Technology, Wiejska 45, 15-351, Białystock, Poland

    Dariusz Kacprzak

  2. Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008, Warsaw, Poland

    Witold Kosiński & W. Konrad Kosiński

  3. Kazimierz Wielki University of Bydgoszcz, Chodkiewicza 30, 85-064, Bydgoszcz, Poland

    Witold Kosiński

Authors
  1. Dariusz Kacprzak
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  2. Witold Kosiński
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  3. W. Konrad Kosiński
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Michiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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Kacprzak, D., Kosiński, W., Kosiński, W.K. (2013). Financial Stock Data and 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_24

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  • DOI: https://doi.org/10.1007/978-3-642-38658-9_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38657-2

  • Online ISBN: 978-3-642-38658-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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