Deduction of initial strategy distributions of agents in mix-game models

This paper reports the effort of deducing the initial strategy distributions (ISDs) of agents in mix-game models that is used to predict a real financial time series generated from a target financial market. Using mix-games to predict Shanghai Index, we find that the time series of prediction accurate rates is sensitive to the ISDs of agents in group 2 who play a minority game, but less sensitive to the ISDs of agents in group 1 who play a majority game. And agents in group 2 tend to cluster in full strategy space (FSS) if the real financial time series has obvious tendency (upward or downward), otherwise they tend to scatter in FSS. We also find that the ISDs and the number of agents in group 1 influence the level of prediction accurate rates. Finally, this paper gives suggestion about further research.     

Mass renormalization and runaway solutions

Zeitschrift für Physik B Condensed Matter - The relationship between negative mechanical mass and runaway solutions is studied using the model of a charged spherical shell. The model yields...     

Mean relaxation time approximation for dynamical correlation functions in stochastic systems near instabilities

The linewidth factor of the order parameter autocorrelation function for the mean fieldn-vector Ginzburg-Landau model is determined numerically forn>2. This generalizes results for the single mode laser (n=2) obtained in Part II [Nadler, W., Schulten, K.: Z. Phys. B—Condensed Matter].     

A long-range memory stochastic model of the return in financial markets

We present a nonlinear stochastic differential equation (SDE) which mimics the probability density function (PDF) of the return and the power spectrum of the absolute return in financial markets. Absolute return as a measure of market volatility is considered in the proposed model as a long-range memory stochastic variable. The SDE is obtained from the analogy with an earlier proposed model of trading activity in the financial markets and generalized within the nonextensive statistical mechanics framework. The proposed stochastic model generates time series of the return with two power law statistics, i.e., the PDF and the power spectral density, reproducing the empirical data for the one-minute trading return in the NYSE.     

Some kind of Anderson transition in one-dimensional disordered systems and the Ioffe-Regel criterion

Zeitschrift für Physik B Condensed Matter - Electron localization in 1d Frish-Lloyd model is investigated atp Fl∼1 using the Berezinsky diagram technique. The localization lengthl loc...     

Solution of the Pauli-equation for neutrons in varying magnetic fields and its application to reflection and transmission at helical magnetic structures

Zeitschrift für Physik B Condensed Matter - The behaviour of neutrons in magnetic fields varying harmonically in time or space is treated. For the case of time-dependent fields the movement of...     

Soliton excitations in the molecular-crystal model in a ring threaded by an Aharonov-Bohm flux

Zeitschrift für Physik B Condensed Matter - Effects of the Aharonov-Bohm flux on soliton excitations in the molecular-crystal model with the dispersion term in a one-dimensional ring are...     

System dynamics of behaviour-evolutionary mix-game models

In real financial markets there are two kinds of traders:one is fundamentalist,and the other is a trend-follower.The mix-game model is proposed to mimic such phenomena.In a mix-game model there are two groups of agents:Group 1 plays the majority game and Group 2 plays the minority game.In this paper,we investigate such a case that some traders in real financial markets could change their investment behaviours by assigning the evolutionary abilities to agents:if the winning rates of agents are smaller than a threshold,they will join the other group;and agents will repeat such an evolution at certain time intervals.Through the simulations,we obtain the following findings:(i) the volatilities of systems increase with the increase of the number of agents in Group 1 and the times of behavioural changes of all agents;(ii) the performances of agents in both groups and the stabilities of systems become better if all agents take more time to observe their new investment behaviours;(iii) there are two-phase zones of market and non-market and two-phase zones of evolution and non-evolution;(iv) parameter configurations located within the cross areas between the zones of markets and the zones of evolution are suited for simulating the financial markets.     

Illusion of control in a Brownian game

Both single-player Parrondo games (SPPG) and multi-player Parrondo games (MPPG) display the Parrondo effect (PE) wherein two or more individually fair (or losing) games yield a net winning outcome if alternated periodically or randomly. (There is a more formal, less restrictive definition of the PE.) We illustrate that, when subject to an elementary optimization rule, the PG displays degraded rather than enhanced returns. Optimization provides only the illusion of control, when low-entropy strategies (i.e., which use more information) under-perform random strategies (with maximal entropy). This illusion is unfortunately widespread in many human attempts to manage or predict complex systems. For the PG, the illusion is especially striking in that the optimization rule reverses an already paradoxical-seeming positive gain—the Parrondo effect proper—and turns it negative. While this phenomenon has been previously demonstrated using somewhat artificial conditions in the MPPG [L. Dinis, J.M.R. Parrondo, Europhys. Lett. 63 (2003) 319; J.M.R. Parrondo, L. Dinis, J. Buceta, K. Lindenberg, Advances in Condensed Matter and Statistical Mechanics, E. Korutcheva, R. Cuerno (Eds.), Nova Science Publishers, New York, 2003], we demonstrate it in the natural setting of a history-dependent SPPG.     

Multiscale Entropy under the Inverse Gaussian Distribution： Analytical Results

The multiscale entropy （MSE） reveals the intrinsic multiple scales in the complexity of physical and physiological signals, which are usually featured by heavy-tailed distributions. However, most research results are pure experimental search. Recently, Costa et al. have made the first attempt to present the theoretical basis of MSE, but it only supports the Gaussian distribution [Phys Rev. E 71 （2005） 021906]. We present the theoretical basis of MSE under the inverse Gaussian distribution, a typical model for physiological, physical and financial data sets. The analysis allows for uncorrelated inverse Gaussian process and 1/f noise with the multivariate inverse Gaussian distribution, and then provides a reliable foundation for the potential applications of MSE to explore complev nhwical and Dhwical time series.     

Magnetic gap and magnetization curve for a mixed valent semiconductor: A variational approach

Zeitschrift für Physik B Condensed Matter - The ground state properties of the nondegenerate periodic Anderson model, which includes an external magnetic field, are studied variationally. We...     

Free energy and excitation spectrum of a one-dimensional fermi system

Zeitschrift für Physik B Condensed Matter - The free energy of a 1-d system of spin 1/2 fermions is studied by means of a perturbation expansion with respect to the spin-flip backward...     

Autocorrelation type,timescale and statistical property in financial time series

Earlier studies have documented that three types of autocorrelations exist in financial time series: sign, volatility, and return autocorrelation. In this paper, we examine how each type of the above autocorrelations affects the statistical properties of financial time series and its role in maintaining such statistical properties. Using three different shuffling series that correspondingly destroy each type of autocorrelation upon different timescales, we find that: (1) the statistical properties of the shuffling series significantly vary from the original ones; (2) volatility and return autocorrelations show greater impacts than sign autocorrelation; (3) the effects on the statistical properties are intensified as time scale expands; (4) the nonlinear component of autocorrelation is the major drive of the effect.     

Modelling fluctuations of financial time series: from cascade process to stochastic volatility model

In this paper, we provide a simple, “generic” interpretation of multifractal scaling laws and multiplicative cascade process paradigms in terms of volatility correlations. We show that in this context 1/f power spectra, as recently observed in reference [23], naturally emerge. We then propose a simple solvable “stochastic volatility” model for return fluctuations. This model is able to reproduce most of recent empirical findings concerning financial time series: no correlation between price variations, long-range volatility correlations and multifractal statistics. Moreover, its extension to a multivariate context, in order to model portfolio behavior, is very natural. Comparisons to real data and other models proposed elsewhere are provided. Received 22 May 2000     

金融市场中经纪人相互竞争和适应性行为的物理模型

金融物理中的争当少数者博奕模型,是一个用来模拟金融市场动力学行为的最简单的模型,可以尝试利用它来对实际金融市场中许多现象提供物理的理解.文章介绍了关于金融物理的争当少数者博奕模型的一些主要研究结果和若干最新的发展方向.     

Multidimensional infinitely divisible cascades

The framework of infinitely divisible scaling was first developed to analyse the statistical intermittency of turbulence in fluid dynamics. It also reveals a powerful tool to describe and model various situations including Internet traffic, financial time series, textures ... A series of recent works introduced the infinitely divisible cascades in 1 dimension, a family of multifractal processes that can be easily synthesized numerically. This work extends the definition of infinitely divisible cascades from 1 dimension to d dimensions in the scalar case. Thus, a class of models is proposed both for data analysis and for numerical simulation in dimension d≥1. In this article, we give the definitions and main properties of infinitely divisible cascades in d dimensions. Then we focus on the modelling of statistical intermittency in turbulent flows. Several other applications are considered.     

Interstitialcy theory of simple condensed matter

A simple, more physical and compelling version of the Interstitialcy Theory of Simple Condensed Matter than that given previously is provided here. Also, computer simulation and direct and indirect experimental evidence is updated and reviewed. The theory is based on the properties of an interstitial in the interstitialcy, sometimes known as the dumbbell configuration. A free energy is derived, taking account of the unusually large shear susceptibility and vibrational entropy of the dumbbell to find the thermodynamic and kinetic properties of simple liquids and glasses. The connection between theory and experiment for some of the more notable properties of simple condensed matter found later is also discussed. The direct visual observation of interstitial diffusion to the surface in platinum near 20 K in irradiated thin films by Morgenstern et al. [M. Morgenstern, T. Michely, G. Comsa, Phys. Rev. Lett. 79, 1305 (1997)] is found to be sufficient compelling evidence for the interstitialcy theory.     

The evaluation of total absorption cross-section for photons in high density electron gas

Zeitschrift für Physik B Condensed Matter - The total absorption cross-section for a photon by an electron gas is calculated in the high density limit. The calculation uses the Green’s...     

Dissipative tunneling

Zeitschrift für Physik B Condensed Matter - The rate of escape of a metastable state is studied in a temperature regime where quantum tunneling acts as the rate limiting process. The particle...     

Dynamics of real financial markets: A reply to Frank’s comment

This reply addresses the assertion in the comment of T.D. Frank [T.D. Frank, Physica A 387 (2008) 773] on our paper [K.E. Bassler, G.H. Gunaratne, J.L. McCauley, Physica A 369 (2006) 343] that the approach to modeling financial markets that we propose is unrealistic. In our paper, we considered variable diffusion processes that have a diffusion coefficient that varies with both position (return in finance) and time, and used them to show that measuring a Hurst exponent H≠1/2 in a time series does not necessarily imply correlations between increments. We also proposed that such a variable diffusion process is the underlying stochastic process governing the dynamics of financial markets. Frank asserts that this is unrealistic because variable diffusion processes with H≠1/2 are driven with a “force” that varies in time as a power law. He claims, instead, that markets obey nonextensive thermostatistics. We discuss evidence from a recently published empirical study of the Euro-Dollar exchange rate [K.E. Bassler, J.L. McCauley, G.H. Gunaratne, PNAS 104 (2007) 17287] that shows that the market can be described with a variable diffusion process, but is inconsistent with nonextensive thermostatistics. This evidence demonstrates that our modeling approach is realistic and accurate.