  In this paper, we quantitatively investigate the properties of a statistical
ensemble of stock prices. We focus attention on the relative price defined as $
X(t) = S(t)/S(0) $, where $ S(0) $ is the initial price. We selected
approximately 3200 stocks traded on the Japanese Stock Exchange and formed a
statistical ensemble of daily relative prices for each trading day in the
3-year period from January 4, 1999 to December 28, 2001, corresponding to the
period in which the {\it internet Bubble} formed and {\it crashes} in the
Japanese stock market. We found that the upper tail of the complementary
cumulative distribution function of the ensemble of the relative prices in the
high value of the price is well described by a power-law distribution, $ P(S>x)
\sim x^{-\alpha} $, with an exponent that moves over time. Furthermore, we
found that as the power-law exponents $ \alpha $ approached {\it two}, the
bubble burst. It is reasonable to assume that when the power-law exponents
approached {\it two}, it indicates the bubble is about to burst.
  PACS: 89.65.Gh; Keywords: Market crashes, Power law, Precursor
