EconoPhysics Papers
https://www3.unifr.ch/econophysics/?q=news/popular
enGlobal dynamics of GDP and trade
https://www3.unifr.ch/econophysics/?q=content/global-dynamics-gdp-and-trade
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>We use the logistic equation to model the dynamics of the GDP and the trade of the six countries with the highest GDP in the world, namely, USA, China, Japan, Germany, UK and India. From the modelling of the economic data, which are made available by the World Bank, we predict the maximum values of the growth of GDP and trade, as well as the duration over which exponential growth can be sustained. We set up the correlated growth of GDP and trade as the phase solutions of an autonomous second-order dynamical system. GDP and trade are related to each other by a power law, whose exponent differentiates the six national economies into two types. Under conducive conditions for economic growth, our conclusions have general validity.</p>
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</div>Tue, 14 Sep 2021 06:35:51 +0000alkapro28039 at https://www3.unifr.ch/econophysicsUnderstanding the nature of the long--range memory phenomenon in socio-economic systems
https://www3.unifr.ch/econophysics/?q=content/understanding-nature-long-range-memory-phenomenon-socio-economic-systems
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>In the face of the upcoming 30th anniversary of econophysics, we review our contributions and other related works on the modeling of the long-range memory phenomenon in physical, economic, and other social complex systems. Our group has shown that the long-range memory phenomenon can be reproduced using various Markov processes, such as point processes, stochastic differential equations and agent-based models. Reproduced well enough to match other statistical properties of the financial markets, such as return and trading activity distributions and first-passage time distributions. Research has lead us to question whether the observed long-range memory is a result of actual long-range memory process or just a consequence of non-linearity of Markov processes. As our most recent result we discuss the long-range memory of the order flow data in the financial markets and other social systems from the perspective of the fractional Lèvy stable motion. We test widely used long-range memory estimators on discrete fractional Lèvy stable motion represented by the ARFIMA sample series. Our newly obtained results seem indicate that new estimators of self-similarity and long-range memory for analyzing systems with non-Gaussian distributions have to be developed.</p>
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</div>Fri, 06 Aug 2021 08:23:00 +0000Gontis28038 at https://www3.unifr.ch/econophysicsOrder flow in the financial markets from the perspective of the Fractional L\'{e}vy stable motion
https://www3.unifr.ch/econophysics/?q=content/order-flow-financial-markets-perspective-fractional-levy-stable-motion
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><pre>
It is a challenging task to identify the best possible models</pre><pre>
based on given empirical data of real stochastic time series. Though the financial markets provide us with a vast amount of empirical data, the best model selection is still a big challenge for researchers. The widely used long-range memory and self-similarity estimators give varying values of the parameters as these estimators themselves are developed for the specific models of time series. Here we investigate the order disbalance time series constructed from the limit order book data of the financial markets under fractional L\'{e}vy stable motion assumption. Our results suggest that previous findings of persistence in order flow are related to the power-law distribution of order sizes. Still, orders have stable estimates of anti-correlation for the 18 randomly selected stocks, when Absolute value and Higuchi's estimators are implemented. The burst duration analysis based on the first passage problem of time series and implemented in this research gives different estimates of the Hurst parameter more consistent with the uncorrelated increment cases.</pre></div></div></div><div class="vote_block">
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</div>Thu, 06 May 2021 13:51:10 +0000Gontis28037 at https://www3.unifr.ch/econophysicsStrategically positioning cooperators can facilitate the contagion of cooperation
https://www3.unifr.ch/econophysics/?q=content/strategically-positioning-cooperators-can-facilitate-contagion-cooperation
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><div>
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<p>The spreading of cooperation in structured population is a challenging problem which can be observed at different scales of social and biological organization. Generally, the problem is studied by evaluating the chances that few initial invading cooperators, randomly appearing in a network, can lead to the spreading of cooperation. In this paper we demonstrate that in many scenarios some cooperators are more influential than others and their initial positions can facilitate the spreading of cooperation. We investigate six different ways to add initial cooperators in a network of cheaters, based on different network-based measurements. Our research reveals that strategically positioning the initial cooperators in a population of cheaters allows to decrease the number of initial cooperators necessary to successfully seed cooperation. The strategic positioning of initial cooperators can also help to shorten the time necessary for the restoration of cooperation. The optimal ways in which the initial cooperators should be placed is, however, non-trivial in that it depends on the degree of competition, the underlying game, and the network structure. Overall, our results show that, in structured populations, few cooperators, well positioned in strategically chosen places, can spread cooperation faster and easier than a large number of cooperators that are placed badly.</p>
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</div>Thu, 14 Jan 2021 14:42:04 +0000mcavaliere28036 at https://www3.unifr.ch/econophysicsOn Forecasts of the COVID-19 Pandemic
https://www3.unifr.ch/econophysics/?q=content/forecasts-covid-19-pandemic
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>The current COVID-19 pandemic creates seemingly chaotic devastations. Scientists worldwide have failed to predict actual outcomes. A comprehensive study by (Ioannidis, et.al. 2020) examines detailed reasons for the failures. A second study (Taleb, et.al 2020) questions the approaches used for pandemic prediction. They find that the pandemic distribution has a fat tail, and proclaim this result has significant implication for pandemic predictions. The latter study used the Generalized Pareto Distribution. This study examines the historical pandemic series using the truncated Pareto I distribution. It uses the least-squares-fit estimate for this distribution to determine a precise estimate of the tail exponent 1.15. This study uses Monte Carlo techniques to generate synthetic power law series with this exponent. Applying extreme value theory, it compares the characteristics of the pandemic series to that of power law synthetics. The comparisons show excellent agreement between the historical pandemic series and the synthetic ones. This shows that the pandemic’s distribution behaves like the synthetics with this power law, confirming that this distribution is likely to have a fat tail. This study then examines the worldwide countries’ mortality rates in ways similar to those used for the historical pandemic. It finds that this distribution may also have a fat tail with exponent 1.45. This work notes that the historical pandemic distribution is fixed, while it shows that the distribution of the mortality rates continually evolves. The pandemic and mortality distributions’ power law behaviors red-light their high danger, demanding extreme caution for dealing with plagues. However, the fat-tailed distributions cannot make specific predictions. Improved forecasts like those championed by (Ioannidis, et.al. 2020) may provide useful guidance for and aid in monitoring the worldwide countries’ individual pandemic responses.</p>
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</div>Wed, 11 Nov 2020 20:32:25 +0000t.j.mazurek28035 at https://www3.unifr.ch/econophysicsModel of continuous random cascade processes in financial markets
https://www3.unifr.ch/econophysics/?q=content/model-continuous-random-cascade-processes-financial-markets
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>This article present a continuous cascade model of volatility formulated as a stochastic differential equation. Two independent Brownian motions are introduced as random sources triggering the volatility cascade. One multiplicatively combines with volatility; the other does so additively. Assuming that the latter acts perturbatively on the system, then the model parameters are estimated by application to an actual stock price time series. Numerical calculation of the Fokker--Planck equation derived from the stochastic differential equation is conducted using the estimated values of parameters. The results reproduce the pdf of the empirical volatility, the multifractality of the time series, and other empirical facts.</p>
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</div>Tue, 27 Oct 2020 08:25:19 +0000jmaskawa28034 at https://www3.unifr.ch/econophysicsAn Elementary Humanomics Approach to Boundedly Rational Quadratic Models
https://www3.unifr.ch/econophysics/?q=content/elementary-humanomics-approach-boundedly-rational-quadratic-models
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>We take a refreshing new look at boundedly rational quadratic models in economics using some elementary modeling of the principles put forward in the book Humanomics by Vernon L. Smith and Bart J. Wilson. A simple model is introduced built on the fundamental Humanomics principles of gratitude/resentment felt and the corresponding action responses of reward/punishment in the form of higher/lower payoff transfers. There are two timescales: one for strictly self-interested action, as in economic equilibrium, and another governed by feelings of gratitude/resentment. One of three timescale scenarios is investigated: one where gratitude/resentment changes much more slowly than economic equilibrium ("quenched model"). Another model, in which economic equilibrium occurs over a much slower time than gratitude/resent evolution ("annealed" model) is set up, but not investigated. The quenched model with homogeneous interactions turns out to be a non-frustrated spin-glass model. A two-agent quenched model with heterogeneous aligning (ferromagnetic) interactions is analyzed and yields new insights into the critical quenched probability p (1 − p) that represents the empirical frequency of opportunity for agent i to take action for the benefit (hurt) of other that invokes mutual gratitude (resentment). A critical quenched probability p*_i , i = 1, 2, exists for each agent. When p < p*_i , agent i will choose action in their self-interest. When p > p*_i , agent i will take action sensitive to their interpersonal feelings of gratitude/resentment and thus reward/punish the initiating benefit/hurt. We find that the p*_i are greater than one-half, which implies agents are averse to resentful behavior and punishment. This was not built into the model, but is a result of its properties, and consistent with Axiom 4 in Humanomics about the asymmetry of gratitude and resentment. Furthermore, the agent who receives less payoff is more averse to resentful behavior; i.e., has a higher critical quenched probability. For this particular model, the Nash equilibrium has no predictive power of Humanomics properties since the rewards are the same for self-interested behavior, resentful behavior, and gratitude behavior. Accordingly, we see that the boundedly rational Gibbs equilibrium does indeed lead to richer properties.</p>
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</div>Wed, 26 Aug 2020 20:29:55 +0000mjcampbell28033 at https://www3.unifr.ch/econophysicsBoundedly-Rational Fast-Tuning Control Theory and Statistical Mechanics
https://www3.unifr.ch/econophysics/?q=content/boundedly-rational-fast-tuning-control-theory-and-statistical-mechanics
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>We construct a model of control theory with 'fast-tuning' of parameters relative to the ambient dynamics of the system. The parameters are tuned 'myopically' (i.e., small changes are made), along with a random perturbation that allows for a large net change with certain probability. This is modeled using a drift-diffusion stochastic partial differential equation. The idea is to model 'bounded rationality' of the agent(s) tuning the parameters-that is, they may not follow the optimal path for tuning because of a lack of complete information about the system, errors in judgement, and/or a desire to experiment and test other options.</p>
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</div>Wed, 26 Aug 2020 20:27:44 +0000mjcampbell28032 at https://www3.unifr.ch/econophysicsSpurious memory in non-equilibrium stochastic models of imitative behavior
https://www3.unifr.ch/econophysics/?q=content/spurious-memory-non-equilibrium-stochastic-models-imitative-behavior
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>The origin of the long-range memory in the non-equilibrium systems is still an open problem as the phenomenon can be reproduced using models based on Markov processes. In these cases a notion of spurious memory is introduced. A good example of Markov processes with spurious memory is stochastic process driven by a non-linear stochastic differential equation (SDE). This example is at odds with models built using fractional Brownian motion (fBm). We analyze differences between these two cases seeking to establish possible empirical tests of the origin of the observed long-range memory. We investigate probability density functions (PDFs) of burst and inter-burst duration in numerically obtained time series and compare with the results of fBm. Our analysis confirms that the characteristic feature of the processes described by a one-dimensional SDE is the power-law exponent 3/2 of the burst or inter-burst duration PDF. This property of stochastic processes might be used to detect spurious memory in various non-equilibrium systems, where observed macroscopic behavior can be derived from the imitative interactions of agents.</p>
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</div>Thu, 04 Jun 2020 07:39:12 +0000Gontis28031 at https://www3.unifr.ch/econophysicsThe consentaneous model of the financial markets exhibiting spurious nature of long-range memory
https://www3.unifr.ch/econophysics/?q=content/consentaneous-model-financial-markets-exhibiting-spurious-nature-long-range-memory
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>It is widely accepted that there is strong persistence in the volatility of financial time series. The origin of the observed persistence, or long-range memory, is still an open problem as the observed phenomenon could be a spurious effect. Earlier we have proposed the consentaneous model of the financial markets based on the non-linear stochastic differential equations. The consentaneous model successfully reproduces empirical probability and power spectral densities of volatility. This approach is qualitatively different from models built using fractional Brownian motion. In this contribution we investigate burst and inter-burst duration statistics of volatility in the financial markets employing the consentaneous model. Our analysis provides an evidence that empirical statistical properties of burst and inter-burst duration can be explained by non-linear stochastic differential equations driving the volatility in the financial markets. This serves as an strong argument that long-range memory in finance can have spurious nature.</p>
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</div>Thu, 04 Jun 2020 07:33:48 +0000Gontis28030 at https://www3.unifr.ch/econophysicsBessel-like birth-death process
https://www3.unifr.ch/econophysics/?q=content/bessel-birth-death-process
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>We consider models of the population or opinion dynamics which result in the non-linear stochastic differential equations (SDEs) exhibiting the spurious long-range memory. In this context, the correspondence between the description of the birth-death processes as the continuous-time Markov chains and the continuous SDEs is of high importance for the alternatives of modeling. We propose and generalize the Bessel-like birth-death process having clear representation by the SDEs. The new process helps to integrate the alternatives of description and to derive the equations for the probability density function (PDF) of the burst and inter-burst duration of the proposed continuous time birth-death processes.</p>
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</div>Thu, 04 Jun 2020 07:26:57 +0000Gontis28029 at https://www3.unifr.ch/econophysicsLong-range memory test by the burst and inter-burst duration distribution
https://www3.unifr.ch/econophysics/?q=content/long-range-memory-test-burst-and-inter-burst-duration-distribution
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p> It is empirically established that order flow in the financial markets is positively auto-correlated and can serve as an example of a social system with long-range memory. Nevertheless, widely used long-range memory estimators give varying values of the Hurst exponent. We propose the burst and inter-burst duration statistical analysis as one more test of long-range memory and implement it with the limit order book data comparing it with other widely used estimators. This method gives a more reliable evaluation of the Hurst exponent independent of the stock in consideration or time definition used. Results strengthen the expectation that burst and inter-burst duration analysis can serve as a better method to investigate the property of long-range memory.</p>
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</div>Thu, 04 Jun 2020 07:19:05 +0000Gontis28028 at https://www3.unifr.ch/econophysicsInformation Cascades and the Collapse of Cooperation
https://www3.unifr.ch/econophysics/?q=content/information-cascades-and-collapse-cooperation
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><div>
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<p>In various types of structured communities newcomers choose their interaction partners by selecting a role-model and copying their social networks. Participants in these networks may be cooperators who contribute to the prosperity of the community, or cheaters who do not and simply exploit the cooperators. For newcomers it is beneficial to interact with cooperators but detrimental to interact with cheaters. However, cheaters and cooperators usually cannot be identified unambiguously and newcomers’ decisions are often based on a combination of private and public information. We use evolutionary game theory and dynamical networks to demonstrate how the specificity and sensitivity of those decisions can dramatically affect the resilience of cooperation in the community. We show that promiscuous decisions (high sensitivity, low specificity) are advantageous for cooperation when the strength of competition is weak; however, if competition is strong then the best decisions for cooperation are risk-adverse (low sensitivity, high specificity). Opportune decisions based on private and public information can still support cooperation but suffer of the presence of information cascades that damage cooperation, especially in the case of strong competition. Our research sheds light on the way the interplay of specificity and sensitivity in individual decision-making affects the resilience of cooperation in dynamical structured communities.</p>
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</div>Fri, 22 May 2020 08:40:01 +0000mcavaliere28027 at https://www3.unifr.ch/econophysicsPotential in the Schrodinger equation: estimation from empirical data
https://www3.unifr.ch/econophysics/?q=content/potential-schrodinger-equation-estimation-empirical-data
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>A recent model for the stock market calculates future price distributions of a stock as a wave function of a quantum particle conﬁned in an inﬁnite potential well. In such a model the question arose as to how to estimate the classical potential needed for solving the Schrodinger equation. In the present article the method used in that work for evaluating the potential is described, in the simplest version to implement, and more sophisticated implementations are suggested later.</p>
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</div>Mon, 23 Mar 2020 09:34:48 +0000jlsubias28026 at https://www3.unifr.ch/econophysicsRanking the invasions of cheaters in structured populations
https://www3.unifr.ch/econophysics/?q=content/ranking-invasions-cheaters-structured-populations
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>The identification of the most influential individuals in structured populations is an important research question, with many applications across the social and natural sciences. Here, we study this problem in evolutionary populations on static networks, where invading cheaters can lead to the collapse of cooperation. We propose six strategies to rank the invading cheaters and identify those which mostly facilitate the collapse of cooperation. We demonstrate that the type of successful rankings depend on the selection strength, the underlying game, and the network structure. We show that random ranking has generally little ability to successfully identify invading cheaters, especially for the stag-hunt game in scale-free networks and when the selection strength is strong. The ranking based on degree can successfully identify the most influential invaders when the selection strength is weak, while more structured rankings perform better at strong selection. Scale-free networks and strong selection are generally detrimental to the performance of the random ranking, but they are beneficial for the performance of structured rankings. Our research reveals how to identify the most influential invaders using statistical measures in structured communities, and it demonstrates how their success depends on population structure, selection strength, and on the underlying game dynamics.</p>
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</div>Thu, 13 Feb 2020 09:51:24 +0000mcavaliere28025 at https://www3.unifr.ch/econophysicsA Response function of Merton model and Kinetic Ising model
https://www3.unifr.ch/econophysics/?q=content/response-function-merton-model-and-kinetic-ising-model
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>We study contagious defaults of banks by<br />
applying a voting model.<br />
The network of the banks are created by the relation, lending and borrowing among banks.<br />
We introduce the response function from Merton model.<br />
Using this response function we calculate the probability of default (PD) which<br />
includes not only changes of asset values but also the effects of connected banks' defaults using<br />
the mean field approximation.<br />
If we approximate the normal distribution which Merton model uses by $\tanh$ function, we can obtain the kinetic Ising model which represents phase transition.<br />
The asset volatility plays the role of temperature.<br />
In the low temperature limit, the model becomes the threshold model.<br />
We calculate PD which shows an effect of the situations around the bank as the additional PD using the self consistent equation.</p>
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</div>Fri, 13 Dec 2019 08:35:57 +0000hisakadom28024 at https://www3.unifr.ch/econophysicsRelativistic Theory of Value
https://www3.unifr.ch/econophysics/?q=content/relativistic-theory-value
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>On the basis of the theory of fundamental measurements and the relativistic hypothesis on the absence of a dedicated system of values, a space of 1+1 dimension has been constructed, in which each point is associated with a value (object of possible transaction). An illustrative “model of paints” and their mixtures, the values of which correspond to vectors in this space, has been proposed. It has been shown that the transitions from one system of values to another are described, similarly to physics, by the Lorentz transformations. In the proposed model, all classical relativistic effects are present. For inertial motion in the space of models, the principle of maximum benefit has been formulated, which represents an analog of the principle of least action. In the “model of paints”, the value analog of a homogeneous gravity field has been considered, and the simplest problem of dynamics in this field has been solved. The perspectives of generalization of the developed model for the space of 3+1 dimension and the quantum analog of such space have been analyzed.</p>
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</div>Sun, 01 Dec 2019 00:23:42 +0000Melnyk28023 at https://www3.unifr.ch/econophysicsTesting the Goodwin Growth-Cycle Macroeconomic Dynamics in Brazil
https://www3.unifr.ch/econophysics/?q=content/testing-goodwin-growth-cycle-macroeconomic-dynamics-brazil
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>This paper discusses the empirical validity of Goodwin's (1967) macroeconomic model of growth with cycles by assuming that the individual income distribution of the Brazilian society is described by the Gompertz-Pareto distribution (GPD). This is formed by the combination of the Gompertz curve, representing the overwhelming majority of the population (~99%), with the Pareto power law, representing the tiny richest part (~1%). In line with Goodwin's original model, we identify the Gompertzian part with the workers and the Paretian component with the class of capitalists. Since the GPD parameters are obtained for each year and the Goodwin macroeconomics is a time evolving model, we use previously determined, and further extended here, Brazilian GPD parameters, as well as unemployment data, to study the time evolution of these quantities in Brazil from 1981 to 2009 by means of the Goodwin dynamics. This is done in the original Goodwin model and an extension advanced by Desai et al. (2006). As far as Brazilian data is concerned, our results show partial qualitative and quantitative agreement with both models in the studied time period, although the original one provides better data fit. Nevertheless, both models fall short of a good empirical agreement as they predict single center cycles which were not found in the data. We discuss the specific points where the Goodwin dynamics must be improved in order to provide a more realistic representation of the dynamics of economic systems.</p>
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</div>Sat, 23 Nov 2019 05:25:28 +0000mbribeiro28021 at https://www3.unifr.ch/econophysicsTsallis Statistics in the Income Distribution of Brazil
https://www3.unifr.ch/econophysics/?q=content/tsallis-statistics-income-distribution-brazil
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>This paper discusses the empirical evidence of Tsallis statistical functions in the personal income distribution of Brazil. Yearly samples from 1978 to 2014 were linearized by the q-logarithm and straight lines were fitted to the entire range of the income data in all samples, producing a two-parameters-only single function representation of the whole distribution in every year. The results showed that the time evolution of the parameters is periodic and plotting one in terms of the other reveals a cycle mostly clockwise. It was also found that the empirical data oscillate periodically around the fitted straight lines with the amplitude growing as the income values increase. Since the entire income data range can be fitted by a single function, this raises questions on previous results claiming that the income distribution is constituted by a well defined two-classes-base income structure, since such a division in two very distinct income classes might not be an intrinsic property of societies, but a consequence of an a priori fitting-choice procedure that may leave aside possibly important income dynamics at the intermediate levels.</p>
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</div>Sat, 23 Nov 2019 05:20:46 +0000mbribeiro28020 at https://www3.unifr.ch/econophysicsOscillations in the Tsallis Income Distribution
https://www3.unifr.ch/econophysics/?q=content/oscillations-tsallis-income-distribution
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>Oscillations in the complementary cumulative distribution function (CCDF) of individual income data have been found in the data of various countries studied by different authors at different time periods, but the dynamical origins of this behavior are currently unknown. Although these datasets can be fitted by different functions at different income ranges, the Tsallis distribution has recently been found capable of fitting the whole distribution by means of only two parameters. This procedure showed clearly such oscillatory feature in the entire income range feature, but made it particularly visible at the tail of the distribution. Although log-periodic functions fitted to the data are capable of describing this behavior, a different approach to naturally disclose such oscillatory characteristics is to allow the Tsallis <em>q</em>-parameter to become complex. In this paper we use this idea in order to describe the behavior of the CCDF of the Brazilian personal income recently studied empirically by Soares et al. (2016). Typical elements of periodic motion, such as amplitude and angular frequency coupled to this income analysis, were obtained by means of this approach. A highly non-linear function for the CCDF was obtained through this methodology and a numerical test showed it capable of recovering the main oscillatory feature of the original CCDF of the personal income data of Brazil.</p>
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</div>Sat, 23 Nov 2019 05:14:25 +0000mbribeiro28019 at https://www3.unifr.ch/econophysicsRegularities in stock markets
https://www3.unifr.ch/econophysics/?q=content/regularities-stock-markets
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>From the stock markets of six countries with high GDP, we study the stock indices, S&P 500 (NYSE, USA), SSE Composite (SSE, China), Nikkei (TSE, Japan), DAX (FSE, Germany), FTSE 100 (LSE, Britain) and NIFTY (NSE, India). The daily mean growth of the stock values is exponential. The daily price fluctuations about the mean growth are Gaussian, but with a finite asymptotic convergence. The growth of the monthly average of stock values is statistically self-similar to their daily growth. The monthly fluctuations of the price follow a Wiener process, with a decline of the volatility. The mean growth of the daily volume of trade is exponential. These observations are globally applicable and underline regularities across global stock markets.</p>
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</div>Tue, 02 Jul 2019 03:39:13 +0000alkapro28018 at https://www3.unifr.ch/econophysicsSpeculative and Hedging Interaction Model in Oil and U.S. Dollar Markets - Long-Term Investor Dynamics and Phases
https://www3.unifr.ch/econophysics/?q=content/speculative-and-hedging-interaction-model-oil-and-us-dollar-markets-long-term-investor
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>We develop the rational dynamics for the long-term investor among boundedly rational speculators in the Carfi-Musolino speculative and hedging model. Numerical evidence is given that indicates there are various phases determined by the degree of nonrational behavior of speculators. The dynamics are shown to be influenced by speculator "noise". This model has two types of operators: a real economic subject (Air, a long-term trader) and one or more investment banks (Bank, short-term speculators). It also has two markets: oil spot market and U.S. dollar futures. Bank agents react to Air and equilibrate much more quickly than Air, thus we consider rational, best-local-response dynamics for Air based on averaged values of equilibrated Bank variables. The averaged Bank variables are effectively parameters for Air dynamics that depend on deviations-from-rationality (temperature) and Air investment (external field). At zero field, below a critical temperature, there is a phase transition in the speculator system which creates two equilibriums for bank variables, hence in this regime the parameters for the dynamics of the long-term investor Air can undergo a rapid change, which is exactly what happens in the study of quenched dynamics for physical systems. It is also shown that large changes in strategy by the long-term Air investor are always preceded by diverging spatial volatility of Bank speculators. The phases resemble those for unemployment in the "Mark 0" macroeconomic model.</p>
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</div>Tue, 21 May 2019 18:39:05 +0000mjcampbell28016 at https://www3.unifr.ch/econophysicsIdentification of influential invaders in evolutionary populations
https://www3.unifr.ch/econophysics/?q=content/identification-influential-invaders-evolutionary-populations
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>The identification of the most influential nodes has been a vibrant subject of research across the whole of network science. Here we map this problem to structured evolutionary populations, where strategies and the interaction network are both subject to change over time based on social inheritance. We study cooperative communities, which cheaters can invade because they avoid the cost of contributions that are associated with cooperation. The question that we seek to answer is at which nodes cheaters invade most successfully. We propose the weighted degree decomposition to identify and rank the most influential invaders. More specifically, we distinguish two kinds of ranking based on the weighted degree decomposition. We show that a ranking strategy based on negative-weighted degree allows to successfully identify the most influential invaders in the case of weak selection, while a ranking strategy based on positive-weighted degree performs better when the selection is strong. Our research thus reveals how to identify the most influential invaders based on statistical measures in dynamically evolving cooperative communities</p>
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</div>Sun, 19 May 2019 10:36:32 +0000mcavaliere28015 at https://www3.unifr.ch/econophysicsTowards Exact Nonextensive Solutions of the American Style Options 4: Infinitesimal Linear Evolution of the Early Exercise Premium with Respect to the American Derivative Can Lead to Black-Scholes Like Closed Form Solutions.
https://www3.unifr.ch/econophysics/?q=content/towards-exact-nonextensive-solutions-american-style-options-4-infinitesimal-linear-evolution
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>(*A version of this research has recently been published in Physica A vol 550 pgs 124379 date 2020/7/15 and includes numerical results)</p>
<p>We have recently applied several different approaches [5] towards understanding the American style</p>
<p>derivative random boundary and inequality problems and towards possible solutions.</p>
<p>In this letter we present a fourth discussion and result(s). We specifically focus on the early exercise</p>
<p>(risk) premium, this a monetary measure of the early exercise source of secondary non-market</p>
<p>uncertainty, and utilize this idea of monetary valuation of non-market early exercise uncertainty</p>
<p>(risk) to overcome the inequality portfolio and inequality PDE problem. We do this by relating the</p>
<p>equality portfolio of the European style derivative to the American style directly via the A-E=p relation</p>
<p>between American and European derivatives. We furthermore under an assumption of linear variation of</p>
<p>early exercise premium with respect to American option derive an American Black-Scholes like PDE</p>
<p>model and obtain a closed form solution for the same which parallels the traditional Black-Scholes formula.</p>
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</div>Mon, 25 Feb 2019 16:58:13 +0000fredrickmichael28013 at https://www3.unifr.ch/econophysicsQuantum model for price forecasting in Financial Markets
https://www3.unifr.ch/econophysics/?q=content/quantum-model-price-forecasting-financial-markets
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>Bilingual english-spanish edition. Abstract: The present paper describes a practical example in which the probability distribution of the prices of a stock market blue chip is calculated as the wave function of a quantum particle confined in a potential well. This model may naturally explain the operation of several empirical rules used by technical analysts.</p>
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</div>Sat, 23 Feb 2019 20:18:43 +0000jlsubias28011 at https://www3.unifr.ch/econophysicsPhase transition in the Bayesian estimation of the default portfolio
https://www3.unifr.ch/econophysics/?q=content/phase-transition-bayesian-estimation-default-portfolio
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>The probability of default (PD) estimation is an important process for financial institutions. The difficulty of the estimation depends on the correlations between borrowers. In this paper, we introduce a hierarchical Bayesian estimation method using the beta binomial distribution, and consider a multi-year case with a temporal correlation. A phase transition occurs when the temporal correlation decays by power decay. When the power index is less than one, the PD estimator does not converge. It is difficult to estimate the PD with the limited historical data. Conversely, when the power index is greater than one, the convergence is the same as that of the binomial distribution. We provide a condition for the estimation of the PD and discuss the universality class of the phase transition. We investigate the empirical default data history of rating agencies, and their Fourier transformations to confirm the the correlation decay equation. The power spectrum of the decay history seems to be 1/f of the fluctuations that correspond to long memory. But the estimated power index is much greater than one. If we collect adequate historical data, the parameters can be estimated correctly.</p>
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</div>Tue, 19 Feb 2019 00:12:31 +0000hisakadom28010 at https://www3.unifr.ch/econophysics
The anatomy of Reddit: An overview of academic research
https://www3.unifr.ch/econophysics/?q=content/anatomy-reddit-overview-academic-research
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> Online forums provide rich environments where users may post questions and
comments about different topics. Understanding how people behave in online
forums may shed light on the fundamental mechanisms by which collective
thinking emerges in a group of individuals, but it has also important practical
applications, for instance to improve user experience, increase engagement or
automatically identify bullying. Importantly, the datasets generated by the
activity of the users are often openly available for researchers, in contrast
to other sources of data in computational social science. In this survey, we
map the main research directions that arose in recent years and focus primarily
on the most popular platform, Reddit. We distinguish and categorise research
depending on their focus on the posts or on the users, and point to different
types of methodologies to extract information from the structure and dynamics
of the system. We emphasize the diversity and richness of the research in terms
of questions and methods, and suggest future avenues of research.
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</div>Sun, 28 Oct 2018 11:04:11 +0000matus28003 at https://www3.unifr.ch/econophysicsRelevance of backtracking paths in epidemic spreading on networks
https://www3.unifr.ch/econophysics/?q=content/relevance-backtracking-paths-epidemic-spreading-networks
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> The understanding of epidemics on networks has greatly benefited from the
recent application of message-passing approaches, which allow to derive exact
results for irreversible spreading (i.e. diseases with permanent acquired
immunity) in locally-tree like topologies. This success has suggested the
application of the same approach to reversible epidemics, for which an
individual can contract the epidemic and recover repeatedly. The underlying
assumption is that backtracking paths (i.e. an individual is reinfected by a
neighbor he/she previously infected) do not play a relevant role. In this paper
we show that this is not the case for reversible epidemics, since the neglect
of backtracking paths leads to a formula for the epidemic threshold that is
qualitatively incorrect in the large size limit. Moreover we define a modified
reversible dynamics which explicitly forbids direct backtracking events and
show that this modification completely upsets the phenomenology.
</p></div></div></div></div><div class="vote_block">
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</div>Sun, 28 Oct 2018 10:58:05 +0000matus28002 at https://www3.unifr.ch/econophysics
Optimal timescale of community detection in growing networks
https://www3.unifr.ch/econophysics/?q=content/optimal-timescale-community-detection-growing-networks
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> Many social, economic, and information systems can be represented as networks
that grow with time, which makes it challenging to develop and validate methods
to analyze their structure. Static methods are limiting as they miss essential
information on the system's dynamics. On the other hand, methods based on
multi-layer temporal representations of the data lack clear guidelines on how
to partition the input time-stamped data into layers. We focus on the popular
community detection problem, which aims to simplify the description of a given
network by partitioning its nodes into meaningful groups. We use a multi-layer
quality function to show, on both synthetic and real datasets, that the
temporal duration of the layers that leads to optimal communities is tightly
related to the system's intrinsic aging timescale. The use of temporal
information leads to drastically different conclusions on the community
structure of real networks, which challenges our current understanding of the
large-scale organization of growing networks. Our findings point at the
importance of understanding the timescales of the dynamical processes that
generated the observed networks in order to properly assess their structural
patterns.
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</div>Fri, 28 Sep 2018 12:24:49 +0000matus27998 at https://www3.unifr.ch/econophysics
Evolution of Threats in the Global Risk Network
https://www3.unifr.ch/econophysics/?q=content/evolution-threats-global-risk-network
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> With a steadily growing population and rapid advancements in technology, the
global economy is increasing in size and complexity. This growth exacerbates
global vulnerabilities and may lead to unforeseen consequences such as global
pandemics fueled by air travel, cyberspace attacks, and cascading failures
caused by the weakest link in a supply chain. Hence, a quantitative
understanding of the mechanisms driving global network vulnerabilities is
urgently needed. Developing methods for efficiently monitoring evolution of the
global economy is essential to such understanding. Each year the World Economic
Forum publishes an authoritative report on the state of the global economy and
identifies risks that are likely to be active, impactful or contagious. Using a
Cascading Alternating Renewal Process approach to model the dynamics of the
global risk network, we are able to answer critical questions regarding the
evolution of this network. To fully trace the evolution of the network we
analyze the asymptotic state of risks (risk levels which would be reached in
the long term if the risks were left unabated) given a snapshot in time, this
elucidates the various challenges faced by the world community at each point in
time. We also investigate the influence exerted by each risk on others. Results
presented here are obtained through either quantitative analysis or
computational simulations.
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</div>Fri, 28 Sep 2018 12:22:28 +0000matus27997 at https://www3.unifr.ch/econophysics
Dynamic Scaling, Data-collapse and Self-Similarity in Mediation-Driven Attachment Networks
https://www3.unifr.ch/econophysics/?q=content/dynamic-scaling-data-collapse-and-self-similarity-mediation-driven-attachment-networks
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> Recently, we have shown that if the $i$th node of the Barab\'{a}si-Albert
(BA) network is characterized by the generalized degree
$q_i(t)=k_i(t)t_i^\beta/m$, where $k_i(t)\sim t^\beta$ and $m$ are its degree
at current time $t$ and at birth time $t_i$, then the corresponding
distribution function $F(q,t)$ exhibits dynamic scaling. Applying the same idea
to our recently proposed mediation-driven attachment (MDA) network, we find
that it too exhibits dynamic scaling but, unlike the BA model, the exponent
$\beta$ of the MDA model assumes a spectrum of value $1/2\leq \beta \leq 1$.
Moreover, we find that the scaling curves for small $m$ are significantly
different from those of the larger $m$ and the same is true for the BA networks
albeit in a lesser extent. We use the idea of the distribution of inverse
harmonic mean (IHM) of the neighbours of each node and show that the number of
data points that follow the power-law degree distribution increases as the
skewness of the IHM distribution decreases. Finally, we show that both MDA and
BA models become almost identical for large $m$.
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</div>Fri, 28 Sep 2018 12:21:42 +0000matus27996 at https://www3.unifr.ch/econophysicsTowards Exact Nonextensive Solutions Of The American Style Options III: Hamiltonians, Thermodynamics & Gibbs-Bogoliubov Inequalities.
https://www3.unifr.ch/econophysics/?q=content/towards-exact-nonextensive-solutions-american-style-options-iii-hamiltonians-thermodynamics
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>We have recently reported on the issue of uncertainty of exercise inherent to the American style option. This uncertainty results in an inequality between the portfolio and its constituent option and assets (etc.). We have approached this from the point of view of a random boundary in time problem by Green's functions methods in I, and more recently in II as a generalization of the linear programming approach where equalization of the otherwise inequality of the portfolio relation problem is made by introducing a 'slack' function which we identify with the uncertainty of exercise.</p>
<p>In this letter we continue this second approach however from a combined portfolio Black-Scholes approach coupled with an information theoretic and equivalently (maximum) entropy of thermodynamics Hamiltonian superposition view, and the Gibbs-Bogoliubov inequality approach.</p>
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</div>Sat, 15 Sep 2018 16:02:04 +0000fredrickmichael27992 at https://www3.unifr.ch/econophysicsPredicting language diversity with complex networks
https://www3.unifr.ch/econophysics/?q=content/predicting-language-diversity-complex-networks
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>We analyze the model of social interactions with coevolution of the topology and states of the nodes. This model can be interpreted as a model of language change. We propose different rewiring mechanisms and perform numerical simulations for each. Obtained results are compared with the empirical data gathered from two online databases and anthropological study of Solomon Islands. We study the behavior of the number of languages for different system sizes and we find that only local rewiring, i.e. triadic closure, is capable of reproducing results for the empirical data in a qualitative manner. Furthermore, we cancel the contradiction between previous models and the Solomon Islands case. Our results demonstrate the importance of the topology of the network, and the rewiring mechanism in the process of language change.</p>
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</div>Tue, 12 Jun 2018 13:05:36 +0000traducha27991 at https://www3.unifr.ch/econophysics
Querying Complex Networks in Vector Space
https://www3.unifr.ch/econophysics/?q=content/querying-complex-networks-vector-space
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> Learning vector embeddings of complex networks is a powerful approach used to
predict missing or unobserved edges in network data. However, an open challenge
in this area is developing techniques that can reason about
$\textit{subgraphs}$ in network data, which can involve the logical conjunction
of several edge relationships. Here we introduce a framework to make
predictions about conjunctive logical queries---i.e., subgraph
relationships---on heterogeneous network data. In our approach, we embed
network nodes in a low-dimensional space and represent logical operators as
learned geometric operations (e.g., translation, rotation) in this embedding
space. We prove that a small set of geometric operations are sufficient to
represent conjunctive logical queries on a network, and we introduce a series
of increasingly strong implementations of these operators. We demonstrate the
utility of this framework in two application studies on networks with millions
of edges: predicting unobserved subgraphs in a network of drug-gene-disease
interactions and in a network of social interactions derived from a popular web
forum. These experiments demonstrate how our framework can efficiently make
logical predictions such as "what drugs are likely to target proteins involved
with both diseases X and Y?" Together our results highlight how imposing
logical structure can make network embeddings more useful for large-scale
knowledge discovery.
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</div>Fri, 08 Jun 2018 10:09:44 +0000matus27990 at https://www3.unifr.ch/econophysics
Predictive Analysis on Twitter: Techniques and Applications
https://www3.unifr.ch/econophysics/?q=content/predictive-analysis-twitter-techniques-and-applications
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> Predictive analysis of social media data has attracted considerable attention
from the research community as well as the business world because of the
essential and actionable information it can provide. Over the years, extensive
experimentation and analysis for insights have been carried out using Twitter
data in various domains such as healthcare, public health, politics, social
sciences, and demographics. In this chapter, we discuss techniques, approaches
and state-of-the-art applications of predictive analysis of Twitter data.
Specifically, we present fine-grained analysis involving aspects such as
sentiment, emotion, and the use of domain knowledge in the coarse-grained
analysis of Twitter data for making decisions and taking actions, and relate a
few success stories.
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</div>Fri, 08 Jun 2018 10:09:03 +0000matus27989 at https://www3.unifr.ch/econophysics
Growth strategy determines network performance
https://www3.unifr.ch/econophysics/?q=content/growth-strategy-determines-network-performance
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> The interplay between structure and function is critical in determining the
behavior of several systems. Here we propose an adaptive network model inspired
in synaptic pruning that couples activity and topological dynamics. The
coupling creates a discontinuous phase transition between an ordered memory
phase and a disordered one as a function of the transient density. We prove
that the existence of an initial transient period with relatively high density
is critical in providing ordered stationary states that can be used to store
stable memories. We also show that intermediate values of density are optimal
in order to obtain these states with a minimum energy consumption, and that
ultimately it is the transient heterogeneity in the network what determines the
stationary state. Our results here could explain why the pruning curves
observed in actual brain areas present their characteristic temporal profiles
and, eventually, anomalies such as autism and schizophrenia associated,
respectively, with a deficit or excess of pruning.
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</div>Fri, 08 Jun 2018 09:29:53 +0000matus27988 at https://www3.unifr.ch/econophysicsPersistent Intraday Correlations Create Skews in Daily-Scale Distributions Revisited: Behaviors of High-Magnitude Fluctuations
https://www3.unifr.ch/econophysics/?q=content/persistent-intraday-correlations-create-skews-daily-scale-distributions-revisited-behaviors
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>This work began with an earlier study that showed the extreme persistence of intraday correlations in order-flow and price-mobility creates positively skewed daily-scale distributions of bull-bear sentiment and price-change, respectively. The earlier work also dealt with the all-magnitude skew excesses as one of each distribution’s summary parameters and compared scaling behaviors of all corresponding parameters of price-change and sentiment. The present study extends this prior work by determining the price-mobility and order-flow persistent correlations for high magnitude price-changes. This study shows that the bias in daily occurrence probabilities at high-magnitudes determined from price-mobility correlations favors negative price-changes, reversing the positive bias of the all-magnitude probabilities. This produces a negative daily price-mobility skew that creates an equal negative daily price-change distribution’s skew excess at high magnitudes. The behavior of high-magnitude order-flow correlations parallels the behavior of price-mobility described above to create a similar negative sentiment distribution skew at high-magnitudes. The present study then compares behaviors with increasing fluctuation magnitudes of price-change and sentiment skews on the daily and seven-day scale. These scaling comparisons show that the daily negative skew strength at high-magnitudes is amplified at successively higher scales as was the daily positive all-magnitude skew strength in the earlier work. Such amplifications sharply contrast with behaviors of skew strengths for independent identical distributions which must decay with increases in scale.</p>
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</div>Fri, 04 May 2018 00:00:33 +0000t.j.mazurek27983 at https://www3.unifr.ch/econophysics
Generalized Rich-Club Ordering in Networks
https://www3.unifr.ch/econophysics/?q=content/generalized-rich-club-ordering-networks
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> Rich-club ordering refers to tendency of nodes with a high degree to be more
interconnected than expected. In this paper we consider the concept of
rich-club ordering when generalized to structural measures different from the
node degree and to non-structural measures (i.e. to node metadata). The
differences in considering rich-club ordering (RCO) with respect to both
structural and non-structural measures is then discussed in terms of employed
coefficients and of appropriate null models (link rewiring vs metadata
reshuffling). Once defined a framework for the evaluation of generalized
rich-club ordering (GRCO), we investigate such a phenomenon in real networks
provided with node metadata. By considering different notions of node richness
we compare structural and non-structural rich-club ordering, observing how
external information about the network nodes is able to validate the presence
of elites in networked systems.
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</div>Mon, 26 Mar 2018 11:58:50 +0000matus27982 at https://www3.unifr.ch/econophysics
A mathematical model for the spread of multipartite viruses reveals their evolutionary potential
https://www3.unifr.ch/econophysics/?q=content/mathematical-model-spread-multipartite-viruses-reveals-their-evolutionary-potential
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> Multipartite viruses replicate through a puzzling evolutionary strategy.
These viruses have their genomes segmented into two or more parts encapsidated
in separate particles that propagate independently. The requirement of host
co-infection to complete the viral cycle represents a major drawback of this
adaptive strategy, while its advantages remain unclear. Still, multipartitism
is a successful adaptive solution observed in over 40% of all known viral
families, particularly targeting plants. The transition from a monopartite to a
bipartite viral form has been described in vitro under conditions of high
multiplicity of infection, suggesting that cooperation between defective
mutants is a plausible evolutionary pathway towards multipartitism. Here we
devise a compartmental model for the spread of a multipartite virus in a
population of hosts through vector mediated contacts. Our goal is to
disentangle which mechanisms might favor the ecological emergence and
persistence of multipartitism. Our analytical and numerical results uncover a
rich phenomenology driven by the interplay between viral dynamics, vector
driven mobility, and the structure of the host population. In the framework of
our model, multipartitism appears as a successful adaptive strategy driven by
mobility, that permits the colonization of environments forbidden to the
nonsegmented variant. Surprisingly, this is promoted in homogeneous contact
networks, which corresponds to the vast majority of farmed plant patterns. This
is also in line with the observed rising of multipartitism concomitantly with
the agricultural expansion.
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</div>Mon, 26 Mar 2018 11:56:48 +0000matus27981 at https://www3.unifr.ch/econophysics
Analytical study of quality-biased competition dynamics for memes in social media
https://www3.unifr.ch/econophysics/?q=content/analytical-study-quality-biased-competition-dynamics-memes-social-media
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> The spreading of news, memes and other pieces of information occurring via
online social platforms has a strong and growing impact on our modern
societies, with enormous consequences, that may be beneficial but also
catastrophic. In this work we consider a recently introduced model for
information diffusion in social media taking explicitly into account the
competition of a large number of items of diverse quality. We map the meme
dynamics onto a one-dimensional diffusion process that we solve analytically,
deriving the lifetime and popularity distributions of individual memes. We also
present a mean-field type of approach that reproduces the average stationary
properties of the dynamics. In this way we understand and control the role of
the different ingredients of the model, opening the path for the inclusion of
additional, more realistic, features.
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</div>Mon, 26 Mar 2018 11:55:08 +0000matus27980 at https://www3.unifr.ch/econophysicsComplex correlation approach for high frequency financial data
https://www3.unifr.ch/econophysics/?q=content/complex-correlation-approach-high-frequency-financial-data-0
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>We propose a novel approach that allows the calculation of a Hilbert transform based complex correlation for unevenly spaced data. This method is especially suitable for high frequency trading data, which are of a particular interest in finance. Its most important feature is the ability to take into account lead-lag relations on different scales, without knowing them in advance. We also present results obtained with this approach while working on Tokyo Stock Exchange intraday quotations. We show that individual sectors and subsectors tend to form important market components which may follow each other with small but significant delays. These components may be recognized by analysing eigenvectors of complex correlation matrix for Nikkei 225 stocks. Interestingly, sectorial components are also found in eigenvectors corresponding to the bulk eigenvalues, traditionally treated as noise.</p>
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</div>Tue, 06 Mar 2018 10:24:28 +0000mwilinski27978 at https://www3.unifr.ch/econophysicsEconophysics & Stylized Facts of Financial Stock Markets & Nonextensive Derivative Pricing Formulas. Doctoral Thesis Of Fredrick Michael, PhD
https://www3.unifr.ch/econophysics/?q=content/econophysics-stylized-facts-financial-stock-markets-nonextensive-derivative-pricing-formulas
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p>Doctoral Thesis of Fredrick N. Michael, PhD 2002. The PhD thesis covers a dual track candidacy. The first relating to condensed matter theoretical physics, nanometer scale structures, transport, interactions and fields where quantum effects dominate. We obtain detailed descriptions via NEGF non equilibrium Green's functions of quantum non equilibrium transport, coupling of materials, effects of external fields that model spintronics, ballistic transport, and quantum multilayered structures in general.<br />
The second part of the thesis applies the Non extensive entropy and statistics of C. Tsallis to complex and random systems. Specifically we find a nearly perfect stochastic, and statistics of the US S&P500 Standard and Poor's high frequency 500 stocks index and extrapolate to open complex systems inclusive of financial markets in general. Additionally having obtained a highly accurate stochastic differential equation(s) and PDE partial differential equation of the financial market, we generalize the Black-Scholes derivatives pricing theory and formula to the nonextensive statistics accounting for accuracy of the description of the trajectory of the underlying random assets and therefore a highly accurate European style option pricing formula.</p>
<p> </p>
<p><strong>Keywords:</strong> condensed matter, theory, self energy, coupling, non equilibrium, statistics, statistical mechanics, quantum , classical, non extensive, nonextensive, multi layer, spintronics, NEGF non equilibrium Green's functions, ballistic transport, heterostructures, financial markets, stochastic, Ito , nonlinear partial differential equations, Tsallis-Zanette PDE, Fokker-Planck.</p>
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</div>Wed, 21 Feb 2018 19:17:54 +0000fredrickmichael27977 at https://www3.unifr.ch/econophysicsSome stylized facts of the Bitcoin market
https://www3.unifr.ch/econophysics/?q=content/some-stylized-facts-bitcoin-market
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p><p>In recent years a new type of tradable assets appeared, generically known as cryptocurrencies. Among them, the most widespread is Bitcoin. Given its novelty, this paper investigates some statistical properties of the Bitcoin market. This study compares Bitcoin and standard currencies dynamics and focuses on the analysis of returns at different time scales. We test the presence of long memory in return time series from 2011 to 2017, using transaction data from one Bitcoin platform. We compute the Hurst exponent by means of the Detrended Fluctuation Analysis method, using a sliding window in order to measure long range dependence. We detect that Hurst exponents changes significantly during the first years of existence of Bitcoin, tending to stabilize in recent times. Additionally, multiscale analysis shows a similar behavior of the Hurst exponent, implying a self-similar process.</p></p>
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</div>Sun, 28 Jan 2018 20:43:37 +0000aurelio27975 at https://www3.unifr.ch/econophysicsSpurious Seasonality Detection: A Non-Parametric Test Proposal
https://www3.unifr.ch/econophysics/?q=content/spurious-seasonality-detection-non-parametric-test-proposal
<div class="field field-name-abstract field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even"><p><p>This paper offers a general and comprehensive definition of the day-of-the-week effect. Using symbolic dynamics, we develop a unique test based on ordinal patterns in order to detect it. This test uncovers the fact that the so-called “day-of-the-week” effect is partly an artifact of the hidden correlation structure of the data. We present simulations based on artificial time series as well. While time series generated with long memory are prone to exhibit daily seasonality, pure white noise signals exhibit no pattern preference. Since ours is a non-parametric test, it requires no assumptions about the distribution of returns, so that it could be a practical alternative to conventional econometric tests. We also made an exhaustive application of the here-proposed technique to 83 stock indexes around the world. Finally, the paper highlights the relevance of symbolic analysis in economic time series studies.</p></p>
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</div>Sun, 28 Jan 2018 20:33:34 +0000aurelio27974 at https://www3.unifr.ch/econophysics
The Network of U.S. Mutual Fund Investments: Diversification, Similarity and Fragility throughout the Global Financial Crisis
https://www3.unifr.ch/econophysics/?q=content/network-us-mutual-fund-investments-diversification-similarity-and-fragility-throughout-0
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> Network theory proved recently to be useful in the quantification of many
properties of financial systems. The analysis of the structure of investment
portfolios is a major application since their eventual correlation and overlap
impact the actual risk diversification by individual investors. We investigate
the bipartite network of US mutual fund portfolios and their assets. We follow
its evolution during the Global Financial Crisis and analyse the interplay
between diversification, as understood in classical portfolio theory, and
similarity of the investments of different funds. We show that, on average,
portfolios have become more diversified and less similar during the crisis.
However, we also find that large overlap is far more likely than expected from
models of random allocation of investments. This indicates the existence of
strong correlations between fund portfolio strategies. We introduce a
simplified model of propagation of financial shocks, that we exploit to show
that a systemic risk component origins from the similarity of portfolios. The
network is still vulnerable after crisis because of this effect, despite the
increase in the diversification of portfolios. Our results indicate that
diversification may even increase systemic risk when funds diversify in the
same way. Diversification and similarity can play antagonistic roles and the
trade-off between the two should be taken into account to properly assess
systemic risk.
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</div>Thu, 11 Jan 2018 12:34:53 +0000matus27971 at https://www3.unifr.ch/econophysics
The Network of U.S. Mutual Fund Investments: Diversification, Similarity and Fragility throughout the Global Financial Crisis
https://www3.unifr.ch/econophysics/?q=content/network-us-mutual-fund-investments-diversification-similarity-and-fragility-throughout
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> Network theory proved recently to be useful in the quantification of many
properties of financial systems. The analysis of the structure of investment
portfolios is a major application since their eventual correlation and overlap
impact the actual risk diversification by individual investors. We investigate
the bipartite network of US mutual fund portfolios and their assets. We follow
its evolution during the Global Financial Crisis and analyse the interplay
between diversification, as understood in classical portfolio theory, and
similarity of the investments of different funds. We show that, on average,
portfolios have become more diversified and less similar during the crisis.
However, we also find that large overlap is far more likely than expected from
models of random allocation of investments. This indicates the existence of
strong correlations between fund portfolio strategies. We introduce a
simplified model of propagation of financial shocks, that we exploit to show
that a systemic risk component origins from the similarity of portfolios. The
network is still vulnerable after crisis because of this effect, despite the
increase in the diversification of portfolios. Our results indicate that
diversification may even increase systemic risk when funds diversify in the
same way. Diversification and similarity can play antagonistic roles and the
trade-off between the two should be taken into account to properly assess
systemic risk.
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</div>Thu, 11 Jan 2018 12:34:53 +0000matus27970 at https://www3.unifr.ch/econophysics
Generalized Network Dismantling
https://www3.unifr.ch/econophysics/?q=content/generalized-network-dismantling
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> Finding the set of nodes, which removed or (de)activated can stop the spread
of (dis)information, contain an epidemic or disrupt the functioning of a
corrupt/criminal organization is still one of the key challenges in network
science. In this paper, we introduce the generalized network dismantling
problem, which aims to find the set of nodes that, when removed from a network,
results in a network fragmentation into subcritical network components at
minimum cost. For unit costs, our formulation becomes equivalent to the
standard network dismantling problem. Our non-unit cost generalization allows
for the inclusion of topological cost functions related to node centrality and
non-topological features such as the price, protection level or even social
value of a node. In order to solve this optimization problem, we propose a
method, which is based on the spectral properties of a novel node-weighted
Laplacian operator. The proposed method is applicable to large-scale networks
with millions of nodes. It outperforms current state-of-the-art methods and
opens new directions in understanding the vulnerability and robustness of
complex systems.
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</div>Thu, 11 Jan 2018 12:33:21 +0000matus27969 at https://www3.unifr.ch/econophysics
Multiplex core-periphery organization of the human connectome
https://www3.unifr.ch/econophysics/?q=content/multiplex-core-periphery-organization-human-connectome
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> The behavior of many complex systems is determined by a core of densely
interconnected units. While many methods are available to identify the core of
a network when connections between nodes are all of the same type, a principled
approach to define the core when multiple types of connectivity are allowed is
still lacking. Here we introduce a general framework to define and extract the
core-periphery structure of multi-layer networks by explicitly taking into
account the connectivity of the nodes at each layer. We show how our method
works on synthetic networks with different size, density, and overlap between
the cores at the different layers. We then apply the method to multiplex brain
networks whose layers encode information both on the anatomical and the
functional connectivity among regions of the human cortex. Results confirm the
presence of the main known hubs, but also suggest the existence of novel brain
core regions that have been discarded by previous analysis which focused
exclusively on the structural layer. Our work is a step forward in the
identification of the core of the human connectome, and contributes to shed
light to a fundamental question in modern neuroscience.
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</div>Thu, 11 Jan 2018 12:32:28 +0000matus27968 at https://www3.unifr.ch/econophysics
Priority Attachment: a Universal Mechanism for Generating Networks
https://www3.unifr.ch/econophysics/?q=content/priority-attachment-universal-mechanism-generating-networks
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> We claim that networks are created according to the priority attachment
mechanism and we show a simple model which uses the priority attachment to
generate both synthetic and close to empirical networks. Priority attachment is
a mechanism which generalizes previously proposed mechanisms, such as small
world creation or preferential attachment, but we also observe its presence in
a range of real-world networks. In this paper we show that by using priority
attachment we can generate networks of very diverse topologies, as well as
recreate empirical networks. An additional advantage of the priority attachment
mechanism is an easy interpretation of the latent processes of network
formation. We substantiate our claims by performing numerical experiments on
synthetic and empirical networks. The two main contributions of the paper are:
the introduction of the priority attachment mechanism, and the design of the
Priority Rank: a simple network generative model based on the priority
attachment mechanism.
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</div>Thu, 11 Jan 2018 12:30:51 +0000matus27967 at https://www3.unifr.ch/econophysics
Scale-free networks are rare
https://www3.unifr.ch/econophysics/?q=content/scale-free-networks-are-rare
<div class="field field-name-field-serial-no field-type-arxiv field-label-hidden"><div class="field-items"><div class="field-item even"><div class="arxiv"><p> A central claim in modern network science is that real-world networks are
typically "scale free," meaning that the fraction of nodes with degree $k$
follows a power law, decaying like $k^{-\alpha}$, often with $2 < \alpha < 3$.
However, empirical evidence for this belief derives from a relatively small
number of real-world networks. We test the universality of scale-free structure
by applying state-of-the-art statistical tools to a large corpus of nearly 1000
network data sets drawn from social, biological, technological, and
informational sources. We fit the power-law model to each degree distribution,
test its statistical plausibility, and compare it via a likelihood ratio test
to alternative, non-scale-free models, e.g., the log-normal. Across domains, we
find that scale-free networks are rare, with only 4% exhibiting the
strongest-possible evidence of scale-free structure and 52% exhibiting the
weakest-possible evidence. Furthermore, evidence of scale-free structure is not
uniformly distributed across sources: social networks are at best weakly scale
free, while a handful of technological and biological networks can be called
strongly scale free. These results undermine the universality of scale-free
networks and reveal that real-world networks exhibit a rich structural
diversity that will likely require new ideas and mechanisms to explain.
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</div>Thu, 11 Jan 2018 12:30:25 +0000matus27966 at https://www3.unifr.ch/econophysics