Jones industrial average index (DJIA) for different periods of their historical daily data. We have analyzed the returns … autocorrelation function (ACF) and used detrended fluctuation analysis (DFA) to study returns variations. We also analyze the … volatility, mean value and standard deviation of both markets and compare their evolution. We conclude from the overall result of …

. We apply these statistics to the distribution of returns of one century of daily data for the Dow Jones Industrial … suggest that the structure of the tails of the distributions of returns is more complex than usually assumed; it is clearly …

We study the probability distribution of stock returns at mesoscopic time lags (return horizons) ranging from about an … function is determined by the variance of returns, which increases proportionally to the time lag. At longer times, the … analytical solution of the Heston model with stochastic volatility. …

In high frequency financial data not only returns but also waiting times between trades are random variables. In this …

investment strategies for such indices. We show the time dependence of the returns. …

the Japanese financial market. The dynamical behavior of returns and volatilities in this case is particularly treated at … the long-time limit. We find that the volatility for prices shows a power-law with anomalous scaling exponents κ=0.92 (1 …

stochastic volatility. The description of the unconditional distribution for the absolute returns is in good agreement with the … volatility clusters are described by a scaling law for the distribution of returns conditional to the value at the previous day …We apply an asymmetric version of Kirman's herding model to volatile financial markets. In the relation between returns …