Fractal structure of financial high frequency data

研究成果: Article査読

11 被引用数 (Scopus)

抄録

We propose a new method to describe scaling behavior of time series. We introduce an extension of extreme values. Using these extreme values determined by a scale, we define some functions. Moreover, using these functions, we can measure a kind of fractal dimension - fold dimension. In financial high frequency data, observations can occur at varying time intervals. Using these functions, we can analyze non-equidistant data without interpolation or evenly sampling. Further, the problem of choosing the appropriate time scale is avoided. Lastly, these functions are related to a viewpoint of investor whose transaction costs coincide with the spread.

本文言語English
ページ(範囲)13-18
ページ数6
ジャーナルFractals
10
1
DOI
出版ステータスPublished - 2002 8 19
外部発表はい

ASJC Scopus subject areas

  • モデリングとシミュレーション
  • 幾何学とトポロジー
  • 応用数学

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