Inverse Cubic Law for the Probability Distribution of Stock Price Variations
arXiv:cond-mat/9803374 · doi:10.1007/s100510050292
Abstract
The probability distribution of stock price changes is studied by analyzing a database (the Trades and Quotes Database) documenting every trade for all stocks in three major US stock markets, for the two year period Jan 1994 -- Dec 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 approximately 3, well outside the Levy regime 0< alpha <2.
5 pages, 4 figures, RevTex 2 figures added