Correlation structure of extreme stock returns

It is commonly believed that the correlations between stock returns increase in high volatility periods. We investigate how much of these correlations can be explained within a simple non-Gaussian one-factor description with time independent correlations. Using surrogate data with the true market return as the dominant factor, we show that most of these correlations, measured by a variety of different indicators, can be accounted for. In particular, this one-factor model can explain the level and asymmetry of empirical exceedance correlations. However, more subtle effects require an extension of the one factor model, where the variance and skewness of the residuals also depend on the market return.Comment: Substantial rewriting. Added exceedance correlations, removed some confusing material. To appear in Quantitative Financ

Volatility distribution in the S&P500 Stock Index

We study the volatility of the S&P500 stock index from 1984 to 1996 and find that the volatility distribution can be very well described by a log-normal function. Further, using detrended fluctuation analysis we show that the volatility is power-law correlated with Hurst exponent $\alpha\cong0.9$.Comment: 6 pages, 5 figure

Possible Stratification Mechanism in Granular Mixtures

We propose a mechanism to explain what occurs when a mixture of grains of different sizes and different shapes (i.e. different repose angles) is poured into a quasi-two-dimensional cell. Specifically, we develop a model that displays spontaneous stratification of the large and small grains in alternating layers. We find that the key requirement for stratification is a difference in the repose angles of the two pure species, a prediction confirmed by experimental findings. We also identify a kink mechanism that appears to describe essential aspects of the dynamics of stratification.Comment: 4 pages, 4 figures, http://polymer.bu.edu/~hmakse/Home.htm

Correlations in Economic Time Series

The correlation function of a financial index of the New York stock exchange, the S&P 500, is analyzed at 1 min intervals over the 13-year period, Jan 84 -- Dec 96. We quantify the correlations of the absolute values of the index increment. We find that these correlations can be described by two different power laws with a crossover time t_\times\approx 600 min. Detrended fluctuation analysis gives exponents $\alpha_1=0.66$ and $\alpha_2=0.93$ for $t<t_\times$ and $t>t_\times$ respectively. Power spectrum analysis gives corresponding exponents $\beta_1=0.31$ and $\beta_2=0.90$ for $f>f_\times$ and $f< f_\times$ respectively.Comment: 6 pages, 2 figure

Dynamics of a ferromagnetic domain wall and the Barkhausen effect

We derive an equation of motion for the the dynamics of a ferromagnetic domain wall driven by an external magnetic field through a disordered medium and we study the associated depinning transition. The long-range dipolar interactions set the upper critical dimension to be $d_c=3$, so we suggest that mean-field exponents describe the Barkhausen effect for three-dimensional soft ferromagnetic materials. We analyze the scaling of the Barkhausen jumps as a function of the field driving rate and the intensity of the demagnetizing field, and find results in quantitative agreement with experiments on crystalline and amorphous soft ferromagnetic alloys.Comment: 4 RevTex pages, 3 ps figures embedde

Dynamics of a ferromagnetic domain wall: avalanches, depinning transition and the Barkhausen effect

We study the dynamics of a ferromagnetic domain wall driven by an external magnetic field through a disordered medium. The avalanche-like motion of the domain walls between pinned configurations produces a noise known as the Barkhausen effect. We discuss experimental results on soft ferromagnetic materials, with reference to the domain structure and the sample geometry, and report Barkhausen noise measurements on Fe$_{21}$Co$_{64}$B$_{15}$ amorphous alloy. We construct an equation of motion for a flexible domain wall, which displays a depinning transition as the field is increased. The long-range dipolar interactions are shown to set the upper critical dimension to $d_c=3$, which implies that mean-field exponents (with possible logarithmic correction) are expected to describe the Barkhausen effect. We introduce a mean-field infinite-range model and show that it is equivalent to a previously introduced single-degree-of-freedom model, known to reproduce several experimental results. We numerically simulate the equation in $d=3$, confirming the theoretical predictions. We compute the avalanche distributions as a function of the field driving rate and the intensity of the demagnetizing field. The scaling exponents change linearly with the driving rate, while the cutoff of the distribution is determined by the demagnetizing field, in remarkable agreement with experiments.Comment: 17 RevTeX pages, 19 embedded ps figures + 1 extra figure, submitted to Phys. Rev.