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  • 标题:Diagnostics of a persistence property for quotations dynamics on high-tech stock markets
  • 本地全文:下载
  • 作者:Nataliia Maksyshko ; Oksana Vasylieva
  • 期刊名称:SHS Web of Conferences
  • 印刷版ISSN:2416-5182
  • 电子版ISSN:2261-2424
  • 出版年度:2019
  • 卷号:65
  • 页码:1-6
  • DOI:10.1051/shsconf/20196506009
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:The research purpose is diagnosis of the persistence property for the stock quotes time series of leading companies belonging to the high-tech sector: Apple Inc., Microsoft Corporation and Samsung Electronics Co. The persistence property or the trend-stability of the time series is crucial meaning for the investor. As a result of the application of the R\S-analysis, it is proved that the stock quotations dynamics of these companies have the persistence property. Also, the method of sequential R\S analysis is applied: the leading characteristics of the long-term memory are discovered, which makes it possible to carry out a comparative analysis of their predictability. It is found that the time series of profitability do not have the properties of persistence. However, the tests for diagnostic of a deterministic chaos reveal the appearance of the persistence property in the time series of “delayed” profitability. The obtained results allows to state the fractal nature for the time series of quotations, while the characteristics of the persistence (depth of memory) determined by the research can be useful to the investor in terms of the investment instrument choice and the investment horizon as well as can be used in selecting the parameters for a forecasting model.
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