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  • 标题:A STUDY OF STABLE MODELS OF STOCK MARKETS
  • 本地全文:下载
  • 作者:Igor Belov ; Audrius Kabašinskas ; Leonidas Sakalauskas
  • 期刊名称:Public Policy And Administration
  • 印刷版ISSN:2029-2872
  • 出版年度:2015
  • 卷号:35
  • 期号:1
  • DOI:10.5755/j01.itc.35.1.12033
  • 语种:English
  • 出版社:Kaunas University of Technology
  • 摘要:Since the middle of the last century, financial engineering has become very popular among mathema-ticians and analysts. Stochastic methods were widely applied in financial engineering. Gaussian models were the first to be applied, but it has been noticed out that they inadequately describe the behavior of financial series. Since the classical Gaussian models were taken with more and more criticism and eventually have lost their positions, new models were proposed. Stable models attracted special attention; however their adequacy in real market should be justified. Nowadays, they have become an extremely powerful and versatile tool in financial modeling. Stock market modeling problems are considered in this paper. Adequacy and efficiency of the chosen model are demonstrated. The parameters of stable laws are estimated by the maximal likelihood method. Multifractality and self-similarity hypo-theses are tested and the Hurst analysis is made as well.
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