Inverse Cubic Law for the Probability Distribution of Stock Price   Variations
  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. 
Parameswaran Gopikrishnan, Martin Meyer, Luis A Nunes Amaral and H   Eugene Stanley