• DOI:10.1103/PhysRevE.60.6519
• Corpus ID: 17838855

Scaling of the distribution of price fluctuations of individual companies.

@article{Plerou1999ScalingOT,
  title={Scaling of the distribution of price fluctuations of individual companies.},
  author={Vasiliki Plerou and P. Gopikrishnan and Lu{\'i}s A. Nunes Amaral and Martin Meyer and Harry Eugene Stanley},
  journal={Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics},
  year={1999},
  volume={60 6 Pt A},
  pages={
          6519-29
        }
}

• V. Plerou, P. Gopikrishnan, +2 authors H. Stanley
• Published 10 July 1999
• Economics
• Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics

We present a phenomenological study of stock price fluctuations of individual companies. We systematically analyze two different databases covering securities from the three major U.S. stock markets: (a) the New York Stock Exchange, (b) the American Stock Exchange, and (c) the National Association of Securities Dealers Automated Quotation stock market. Specifically, we consider (i) the trades and quotes database, for which we analyze 40 million records for 1000 U.S. companies for the 2-yr period 1994-95; and (ii) the Center for Research and Security Prices database, for which we analyze 35 million daily records for approximately 16,000 companies in the 35-yr period 1962-96. We study the probability distribution of returns over varying time scales Delta t, where Delta t varies by a factor of approximately 10(5), from 5 min up to approximately 4 yr. For time scales from 5 min up to approximately 16 days, we find that the tails of the distributions can be well described by a power-law decay, characterized by an exponent 2.5 < proportional to < 4, well outside the stable Lévy regime 0 < alpha < 2. For time scales Delta t >> (Delta t)(x) approximately equal to 16 days, we observe results consistent with a slow convergence to Gaussian behavior. We also analyze the role of cross correlations between the returns of different companies and relate these correlations to the distribution of returns for market indices.