This paper illustrates an information theoretic approach for calculating serial dependence within a time series of daily prices. By calculating an index value which indicates the degree of diversity between actual and predicted prices of stocks listed on the Tokyo Stock Exchange, optimal predictors of prices were computed from prior empirical observations. The empirical findings show that serial dependence between successive changes in price for the Tokyo Stock Price Index is surprisingly large.