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At least 19 recordsLinked to original sources

arXiv2007

Statistical analysis of weighted networks

The purpose of this paper is to assess the statistical characterization of weighted networks in terms of the generalization of the relevant parameters, namely average path length, degree distribution and clustering coefficient. Although the degree distribution and the average path length admit straightforward generalizations, for the clustering coefficient several different definitions have been proposed in the literature. We examined the different definitions and identified the similarities and differences between them. In order to elucidate the significance of different definitions of the weighted clustering coefficient, we studied their dependence on the weights of the connections. For this purpose, we introduce the relative perturbation norm of the weights as an index to assess the weight distribution. This study revealed new interesting statistical regularities in terms of the relative perturbation norm useful for the statistical characterization of weighted graphs.

physics.soc-ph↗

arXiv2007

EGT through Quantum Mechanics & from Statistical Physics to Economics

By analyzing the relationships between a socioeconomical system modeled through evolutionary game theory and a physical system modeled through quantum mechanics we show how although both systems are described through two theories apparently different both are analogous and thus exactly equivalents. The extensions of quantum mechanics to statistical physics and information theory let us use some of their definitions for the best understanding of the behavior of economics and biology. The quantum analogue of the replicator dynamics is the von Neumann equation. A system in where all its members are in Nash equilibrium is equivalent to a system in a maximum entropy state. Nature is a game in where its players compete for a common welfare and the equilibrium of the system that they are members. They act as a whole besides individuals like they obey a rule in where they prefer to work for the welfare of the collective besides the individual welfare.

q-fin.GN↗

arXiv2007

The log-normal distribution from Non-Gibrat's law in the middle scale region of profits

Employing profits data of Japanese firms in 2003--2005, we kinematically exhibit the static log-normal distribution in the middle scale region. In the derivation, a Non-Gibrat's law under the detailed balance is adopted together with following two approximations. Firstly, the probability density function of profits growth rate is described as a tent-shaped exponential function. Secondly, the value of the origin of the growth rate distribution divided into bins is constant. The derivation is confirmed in the database consistently. This static procedure is applied to a quasi-static system. We dynamically describe a quasi-static log-normal distribution in the middle scale region. In the derivation, a Non-Gibrat's law under the detailed quasi-balance is adopted together with two approximations confirmed in the static system. The resultant distribution is power-law with varying Pareto index in the large scale region and the quasi-static log-normal distribution in the middle scale region. In the distribution, not only the change of Pareto index but also the change of the variance of the log-normal distribution depends on the parameter of the detailed quasi-balance. As a result, Pareto index and the variance of the log-normal distribution are related to each other.

q-fin.GN↗

arXiv2007

Mykyta the Fox and networks of language

The results of quantitative analysis of word distribution in two fables in Ukrainian by Ivan Franko: "Mykyta the Fox" and "Abu-Kasym's slippers" are reported. Our study consists of two parts: the analysis of frequency-rank distributions and the application of complex networks theory. The analysis of frequency-rank distributions shows that the text sizes are enough to observe statistical properties. The power-law character of these distributions (Zipf's law) holds in the region of rank variable r=20 - 3000 with an exponent $α\simeq 1$. This substantiates the choice of the above texts to analyse typical properties of the language complex network on their basis. Besides, an applicability of the Simon model to describe non-asymptotic properties of word distributions is evaluated. In describing language as a complex network, usually the words are associated with nodes, whereas one may give different meanings to the network links. This results in different network representations. In the second part of the paper, we give different representations of the language network and perform comparative analysis of their characteristics. Our results demonstrate that the language network of Ukrainian is a strongly correlated scale-free small world. Empirical data obtained may be useful for theoretical description of language evolution.

physics.data-an↗

arXiv2009

Correlated multi-asset portfolio optimisation with transaction cost

We employ perturbation analysis technique to study multi-asset portfolio optimisation with transaction cost. We allow for correlations in risky assets and obtain optimal trading methods for general utility functions. Our analytical results are supported by numerical simulations in the context of the Long Term Growth Model.

q-fin.PM↗

arXiv2007

A simple algorithm based on fluctuations to play the market

In Biology, all motor enzymes operate on the same principle: they trap favourable brownian fluctuations in order to generate directed forces and to move. Whether it is possible or not to copy one such strategy to play the market was the starting point of our investigations. We found the answer is yes. In this paper we describe one such strategy and appraise its performance with historical data from the European Monetary System (EMS), the US Dow Jones, the german Dax and the french Cac40.

q-fin.PM↗

arXiv2007

Entropy Oriented Trading: A Trading Strategy Based on the Second Law of Thermodynamics

The author proposes a finance trading strategy named Entropy Oriented Trading and apply thermodynamics on the strategy. The state variables are chosen so that the strategy satisfies the second law of thermodynamics. Using the law, the author proves that the rate of investment (ROI) of the strategy is equal to or more than the rate of price change.

q-fin.TR↗

arXiv2007

Detecting anchoring in financial markets

Anchoring is a term used in psychology to describe the common human tendency to rely too heavily (anchor) on one piece of information when making decisions. A trading algorithm inspired by biological motors, introduced by L. Gil\cite{Gil}, is suggested as a testing ground for anchoring in financial markets. An exact solution of the algorithm is presented for arbitrary price distributions. Furthermore the algorithm is extended to cover the case of a market neutral portfolio, revealing additional evidence that anchoring is involved in the decision making of market participants. The exposure of arbitrage possibilities created by anchoring gives yet another illustration on the difficulty proving market efficiency by only considering lower order correlations in past price time series

q-fin.TR↗

arXiv2007

Network Growth via Preferential Attachment based on Prisoner's Dilemma Game

In this article we discuss network growth based on Prisoner's Dilemma(PD) where palyers on nodes in a network palay with its linked players. The players estimate total profits in the PD. When a new node is attached, the node make linkes to nodes in the network with the probabilities in proportion to the profits made by the game. Iterating this process, a network grows. We investigate properties of this type of growing networks, especially the degree distribution and time-depending strategy distribution by running computer simulation. We also find a sort of phase transition in the strategy distributions. For these phenomena given by computer simulation, theoretical studies are also carried out.

physics.soc-ph↗

arXiv2007

Mixed membership stochastic blockmodels

Observations consisting of measurements on relationships for pairs of objects arise in many settings, such as protein interaction and gene regulatory networks, collections of author-recipient email, and social networks. Analyzing such data with probabilisic models can be delicate because the simple exchangeability assumptions underlying many boilerplate models no longer hold. In this paper, we describe a latent variable model of such data called the mixed membership stochastic blockmodel. This model extends blockmodels for relational data to ones which capture mixed membership latent relational structure, thus providing an object-specific low-dimensional representation. We develop a general variational inference algorithm for fast approximate posterior inference. We explore applications to social and protein interaction networks.

stat.ME↗

arXiv2007

Hiking the hypercube: producers and consumers

We study the dynamics of co-evolution of producers and customers described by bit-strings representing individual traits. Individual ''size-like'' properties are controlled by binary encounters which outcome depends upon a recognition process. Depending upon the parameter set-up, mutual selection of producers and customers results in different types of attractors, either an exclusive niches regime or a competition regime.

q-fin.GN↗

arXiv2007

Heterogeneity and Increasing Returns May Drive Socio-Economic Transitions

There are clear benefits associated with a particular consumer choice for many current markets. For example, as we consider here, some products might carry environmental or `green' benefits. Some consumers might value these benefits while others do not. However, as evidenced by myriad failed attempts of environmental products to maintain even a niche market, such benefits do not necessarily outweigh the extra purchasing cost. The question we pose is, how can such an initially economically-disadvantaged green product evolve to hold the greater share of the market? We present a simple mathematical model for the dynamics of product competition in a heterogeneous consumer population. Our model preassigns a hierarchy to the products, which designates the consumer choice when prices are comparable, while prices are dynamically rescaled to reflect increasing returns to scale. Our approach allows us to model many scenarios of technology substitution and provides a method for generalizing market forces. With this model, we begin to forecast irreversible trends associated with consumer dynamics as well as policies that could be made to influence transitions

q-fin.GN↗

arXiv2007

Nurturing Breakthroughs: Lessons from Complexity Theory

A general theory of innovation and progress in human society is outlined, based on the combat between two opposite forces (conservatism/inertia and speculative herding "bubble" behavior). We contend that human affairs are characterized by ubiquitous ``bubbles'', which involve huge risks which would not otherwise be taken using standard cost/benefit analysis. Bubbles result from self-reinforcing positive feedbacks. This leads to explore uncharted territories and niches whose rare successes lead to extraordinary discoveries and provide the base for the observed accelerating development of technology and of the economy. But the returns are very heterogeneous, very risky and may not occur. In other words, bubbles, which are characteristic definitions of human activity, allow huge risks to get huge returns over large scales. We outline some underlying mathematical structure and a few results involving positive feedbacks, emergence, heavy-tailed power laws, outliers/kings/black swans, the problem of predictability and the illusion of control, as well as some policy implications.

physics.soc-ph↗

arXiv2007

Seeking the best Internet Model

The models of the Internet reported in the literature are mainly aimed at reproducing the scale-free structure, the high clustering coefficient and the small world effects found in the real Internet, while other important properties (e.g. related to centrality and hierarchical measurements) are not considered. For a better characterization and modeling of such network, a larger number of topological properties must be considered. In this work, we present a sound multivariate statistical approach, including feature spaces and multivariate statistical analysis (especially canonical projections), in order to characterize several Internet models while considering a larger set of relevant measurements. We apply such a methodology to determine, among nine complex networks models, which are those most compatible with the real Internet data (on the autonomous systems level) considering a set of 21 network measurements. We conclude that none of the considered models can reproduce the Internet topology with high accuracy.

physics.soc-ph↗

arXiv2007

Epidemic modeling in metapopulation systems with heterogeneous coupling pattern: theory and simulations

The spatial structure of populations is a key element in the understanding of the large scale spreading of epidemics. Motivated by the recent empirical evidence on the heterogeneous properties of transportation and commuting patterns among urban areas, we present a thorough analysis of the behavior of infectious diseases in metapopulation models characterized by heterogeneous connectivity and mobility patterns. We derive the basic reaction-diffusion equation describing the metapopulation system at the mechanistic level and derive an early stage dynamics approximation for the subpopulation invasion dynamics. The analytical description uses degree block variables that allows us to take into account arbitrary degree distribution of the metapopulation network. We show that along with the usual single population epidemic threshold the metapopulation network exhibits a global threshold for the subpopulation invasion. We find an explicit analytic expression for the invasion threshold that determines the minimum number of individuals traveling among subpopulations in order to have the infection of a macroscopic number of subpopulations. The invasion threshold is a function of factors such as the basic reproductive number, the infectious period and the mobility process and it is found to decrease for increasing network heterogeneity. We provide extensive mechanistic numerical Monte Carlo simulations that recover the analytical finding in a wide range of metapopulation network connectivity patterns. The results can be useful in the understanding of recent data driven computational approaches to disease spreading in large transportation networks and the effect of containment measures such as travel restrictions.

q-bio.PE↗

arXiv2007

The minority game: An economics perspective

This paper gives a critical account of the minority game literature. The minority game is a simple congestion game: players need to choose between two options, and those who have selected the option chosen by the minority win. The learning model proposed in this literature seems to differ markedly from the learning models commonly used in economics. We relate the learning model from the minority game literature to standard game-theoretic learning models, and show that in fact it shares many features with these models. However, the predictions of the learning model differ considerably from the predictions of most other learning models. We discuss the main predictions of the learning model proposed in the minority game literature, and compare these to experimental findings on congestion games.

q-fin.GN↗

arXiv2007

The Scientific Method

The nature of the scientific method is controversial with claims that a single scientific method does not even exist. However the scientific method does exist. It is the building of logical and self consistent models to describe nature. The models are constrained by past observations and judged by their ability to correctly predict new observations and interesting phenomena. The observations exist independent of the models but acquire meaning from their context within a model. Observations must be carefully done and reproducible to minimize errors. Models assumptions that do not lead to testable predictions are rejected as unnecessary.

physics.hist-ph↗

arXiv2007

A fast multilevel algorithm for graph clustering and community detection

One of the most useful measures of cluster quality is the modularity of a partition, which measures the difference between the number of the edges joining vertices from the same cluster and the expected number of such edges in a random (unstructured) graph. In this paper we show that the problem of finding a partition maximizing the modularity of a given graph G can be reduced to a minimum weighted cut problem on a complete graph with the same vertices as G. We then show that the resulted minimum cut problem can be efficiently solved with existing software for graph partitioning and that our algorithm finds clusterings of a better quality and much faster than the existing clustering algorithms.

physics.data-an↗