The market efficiency in the stock markets

We study the temporal evolution of the market efficiency in the stock markets using the complexity, entropy density, standard deviation, autocorrelation function, and probability distribution of the log return for Standard and Poor's 500 (S&P 500), Nikkei stock average index, and Korean composition stock price index (KOSPI). Based on the microscopic spin model, we also find that these statistical quantities in stock markets depend on the market efficiency.Comment: 8 pages, 5 figure

Driven Diffusive Systems: How Steady States Depend on Dynamics

In contrast to equilibrium systems, non-equilibrium steady states depend explicitly on the underlying dynamics. Using Monte Carlo simulations with Metropolis, Glauber and heat bath rates, we illustrate this expectation for an Ising lattice gas, driven far from equilibrium by an `electric' field. While heat bath and Glauber rates generate essentially identical data for structure factors and two-point correlations, Metropolis rates give noticeably weaker correlations, as if the `effective' temperature were higher in the latter case. We also measure energy histograms and define a simple ratio which is exactly known and closely related to the Boltzmann factor for the equilibrium case. For the driven system, the ratio probes a thermodynamic derivative which is found to be dependent on dynamics

Efficient sampling of protein structures by model hopping

We introduce a novel simulation method, model hopping, that enhances sampling of low-energy configurations in complex systems. The approach is illustrated for a protein-folding problem. Thermodynamic quantities of proteins with up to 46 residues are evaluated from all-atom simulations with this method. © 2005 The American Physical Society

Generalized-ensemble simulations of all-atom protein models

We review recent progress in generalized-ensemble simulations of proteins. Focusing on the formation of secondary structure, we show how these techniques can lead to a deeper understanding of the folding mechanism in proteins. © 2004 Elsevier B.V. All rights reserved

Optimization of consensus time by combining the voter and the majority voter models on scale-free networks

We introduce a spin model combining the majority voter model with probability p and the voter model with probability $1-p$ and then measure its consensus time on scale-free networks with various degree exponents γ. We find that consensus time depends on both p and γ. When all spins follow either the voter model or the majority voter model, it takes much greater time to reach consensus. On the other hand, when spins may alternate between the majority voter model and the voter model, consensus time is shortened. We find via numerical calculation that the optimized ratio to minimize consensus time is around $p = 0.72$

Critical behavior of the XY model on static scale-free networks

The critical behaviors of the equilibrium model on correlated and uncorrelated networks are known to differ, and the critical behavior of the XY model on correlated scale-free networks has been examined. Here, we study the XY model on uncorrelated scale-free networks with various degree exponents λ of the power law degree distribution P(k)~k$^{- \lambda }$, where the degree k is the number of neighborhood. For λ > 5, we find that the critical exponents of the XY model on uncorrelated networks are identical to those of the standard mean field. These results vary from those derived from correlated networks

The market efficiency in the stock markets

We study the temporal evolution of the market efficiency in the stock markets using the complexity, entropy density, standard deviation, autocorrelation function, and probability distribution of the log return for Standard and Poor's 500 (S&P 500), Nikkei stock average index, and Korean composition stock price index (KOSPI). Based on the microscopic spin model, we also find that these statistical quantities in stock markets depend on the market efficiency.