Inverse cubic law for the distribution of stock price variations
Gopikrishnan P, Meyer M, Amaral LAN, Stanley HEEuropean Physical Journal B 3, 139 - 140 (1998)
Times cited: 271
Abstract
The probability distribution of stock price changes is studied by analysing a database (the Trades and Quotes Database) documenting every trade for all stocks in three major US stock markets, for the two year period January 1994 - December 1995. A sample of 40 million data points is extracted, which is substantially larger than studied hitherto. We find an asymptotic power-law behavior for the cumulative distribution with an exponent alpha approximate to 3, well outside the Levy regime (0 < alpha < 2).