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Medium and small-scale analysis of financial data

Author

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  • Nawroth, Andreas P.
  • Peinke, Joachim

Abstract

A stochastic analysis of financial data is presented. In particular we investigate how the statistics of log returns change with different time delays τ. The scale-dependent behaviour of financial data can be divided into two regions. The first time range, the small-timescale region (in the range of seconds) seems to be characterised by universal features. The second time range, the medium-timescale range from several minutes upwards can be characterised by a cascade process, which is given by a stochastic Markov process in the scale τ. A corresponding Fokker–Planck equation can be extracted from given data and provides a non-equilibrium thermodynamical description of the complexity of financial data.

Suggested Citation

  • Nawroth, Andreas P. & Peinke, Joachim, 2007. "Medium and small-scale analysis of financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 193-198.
    • Handle: RePEc:eee:phsmap:v:382:y:2007:i:1:p:193-198
    DOI: 10.1016/j.physa.2007.03.041
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    Citations

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    Cited by:

    1. Oya, Shunsuke & Aihara, Kazuyuki & Hirata, Yoshito, 2014. "An absolute measure for a key currency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 15-23.
    2. Vindel, Jose M. & Trincado, Estrella, 2010. "The timing of information transmission in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5749-5758.
    3. Wosnitza, Jan Henrik & Leker, Jens, 2014. "Can log-periodic power law structures arise from random fluctuations?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 228-250.
    4. Hirata, Yoshito & Aihara, Kazuyuki, 2012. "Timing matters in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 760-766.

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