  We propose a new approach for analyzing price fluctuations in their strongly
correlated regime ranging from minutes to months. This is done by employing a
self-similarity assumption for the magnitude of coarse-grained price
fluctuation or volatility. The existence of a Cramer function, the
characteristic function for self-similarity, is confirmed by analyzing real
price data from a stock market. We also discuss the close interrelation among
our approach, the scaling-of-moments method and the multifractal approach for
price fluctuations.
