The unique scaling behavior of financial time series have attracted the research interest of physicists. Variables such as stock returns, share volume, and number of trades have been found to display distributions that are consistent with a power-law tail. We present an overview of recent...

We develop a scale-invariant truncated Lévy (STL) process to describe physical systems characterized by correlated stochastic variables. The STL process exhibits Lévy stability for the probability density, and hence shows scaling properties (as observed in empirical data); it has the advantage...

Random magnets provide a paradigm for the study of competing interactions and frustration in physics. Here, we suggest that this paradigm is also useful for the study and explanation of correlations between stock price changes of different companies: it (i) provides for a mechanism to explain...

We investigated the network structures of the Japanese stock market using the minimum spanning tree. We defined a grouping coefficient to test the validity of the conventional grouping by industrial categories, and found a decreasing in trend for the coefficient. This phenomenon supports the...

We discuss some apparently “universal” aspects observed in the empirical analysis of stock price dynamics in financial markets. Specifically we consider (i) the empirical behavior of the return probability density function and (ii) the content of economic information in financial time series.

This manuscript is a brief summary of a talk designed to address the question of whether two of the pillars of the field of phase transitions and critical phenomena—scale invariance and universality—can be useful in guiding research on interpreting empirical data on economic fluctuations....

In recent years, physicists have started applying concepts and methods of statistical physics to study economic problems. The word “Econophysics” is sometimes used to refer to this work. Much recent work is focused on understanding the statistical properties of financial time series. One...