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The Sustainable Development Goals (SDGs) offer a critical global framework for addressing challenges like poverty, inequality, climate change, etc. They encourage a holistic approach integrating economic growth, social inclusion, and environmental sustainability to create a better future. We aim to examine India's responsibility in achieving the SDGs by recognizing the contributions of its diverse states in the federal structure of governance. As the nodal agency in India, the NITI Aayog's existing SDG index, using various socioeconomic indicators to determine the performance across different goals, serves as a foundation for assessing each state's progress. Building on the seminal works of Hidalgo and Hausmann (2009) and Tachhella et al. (2012), which introduced the economic complexity/fitness index, Sciarra et al. (2020) proposed the SDGs-Generalized Economic Complexity (GENEPY) framework to quantify "complexity" by computing "ranks for states" and "scores for goals", treating them as part of a complex bipartite network. In this paper, we apply the SDGs-GENEPY, to evaluate the progress and evolution of Indian states and union territories over several years. This enables us to identify each state's capacity (and rank) in achieving the SDGs. We can interpret these complexity scores as "centrality measures" of a complex bipartite network of the states and the goals. This enhances our understanding of the complex relationship between state capabilities and the achievability of SDGs within the Indian context and enables data-driven policy-making., Comment: 10 pages, 5 figures

The concept of states of financial markets based on correlations has gained increasing attention during the last 10 years. We propose to retrace some important steps up to 2018, and then give a more detailed view of recent developments that attempt to make the use of this more practical. Finally, we try to give a glimpse to the future proposing the analysis of trajectories in correlation matrix space directly or in terms of symbolic dynamics as well as attempts to analyze the clusters that make up the states in a random matrix context., Comment: 16 pages, 9 figures, to appear in the Proceedings Volume, Eds. Anirban Chakraborti, Emmanuel Haven, Sudip Patra and Naresh Singh, "Quantum Decision Theory and Complexity Modelling in Economics and Public Policy" (Springer-Cham, New Economic Windows)

Over the last two decades, financial systems have been studied and analysed from the perspective of complex networks, where the nodes and edges in the network represent the various financial components and the strengths of correlations between them. Here, we adopt a similar network-based approach to analyse the daily closing prices of 69 global financial market indices across 65 countries over a period of 2000-2014. We study the correlations among the indices by constructing threshold networks superimposed over minimum spanning trees at different time frames. We investigate the effect of critical events in financial markets (crashes and bubbles) on the interactions among the indices by performing both static and dynamic analyses of the correlations. We compare and contrast the structures of these networks during periods of crashes and bubbles, with respect to the normal periods in the market. In addition, we study the temporal evolution of traditional market indicators, various global network measures and the recently developed edge-based curvature measures. We show that network-centric measures can be extremely useful in monitoring the fragility in the global financial market indices., Comment: 32 pages, 18 figures, including supplementary material

The complexity of financial markets arise from the strategic interactions among agents trading stocks, which manifest in the form of vibrant correlation patterns among stock prices. Over the past few decades, complex financial markets have often been represented as networks whose interacting pairs of nodes are stocks, connected by edges that signify the correlation strengths. However, we often have interactions that occur in groups of three or more nodes, and these cannot be described simply by pairwise interactions but we also need to take the relations between these interactions into account. Only recently, researchers have started devoting attention to the higher-order architecture of complex financial systems, that can significantly enhance our ability to estimate systemic risk as well as measure the robustness of financial systems in terms of market efficiency. Geometry-inspired network measures, such as the Ollivier-Ricci curvature and Forman-Ricci curvature, can be used to capture the network fragility and continuously monitor financial dynamics. Here, we explore the utility of such discrete Ricci curvatures in characterizing the structure of financial systems, and further, evaluate them as generic indicators of the market instability. For this purpose, we examine the daily returns from a set of stocks comprising the USA S&P-500 and the Japanese Nikkei-225 over a 32-year period, and monitor the changes in the edge-centric network curvatures. We find that the different geometric measures capture well the system-level features of the market and hence we can distinguish between the normal or `business-as-usual' periods and all the major market crashes. This can be very useful in strategic designing of financial systems and regulating the markets in order to tackle financial instabilities., Comment: 34 pages, 17 figures, including Supplementary Material

Distress propagation occurs in connected networks, its rate and extent being dependent on network topology. To study this, we choose economic production networks as a paradigm. An economic network can be examined at many levels: linkages among individual agents (microscopic), among firms/sectors (mesoscopic) or among countries (macroscopic). New emergent dynamical properties appear at every level, so the granularity matters. For viral epidemics, even an individual node may act as an epicenter of distress and potentially affect the entire network. Economic networks, however, are known to be immune at the micro-levels and more prone to failure in the meso/macro-levels. We propose a dynamical interaction model to characterize the mechanism of distress propagation, across different modules of a network, initiated at different epicenters. Vulnerable modules often lead to large degrees of destabilization. We demonstrate our methodology using a unique empirical data-set of input-output linkages across 0.14 million firms in one administrative state of India, a developing economy. The network has multiple hub-and-spoke structures that exhibits moderate disassortativity, which varies with the level of coarse-graining. The novelty lies in characterizing the production network at different levels of granularity or modularity, and finding `too-big-to-fail' modules supersede `too-central-to-fail' modules in distress propagation., Comment: 18 pages, 11 figures

We present a brief overview of random matrix theory (RMT) with the objectives of highlighting the computational results and applications in financial markets as complex systems. An oft-encountered problem in computational finance is the choice of an appropriate epoch over which the empirical cross-correlation return matrix is computed. A long epoch would smoothen the fluctuations in the return time series and suffers from non-stationarity, whereas a short epoch results in noisy fluctuations in the return time series and the correlation matrices turn out to be highly singular. An effective method to tackle this issue is the use of the power mapping, where a non-linear distortion is applied to a short epoch correlation matrix. The value of distortion parameter controls the noise-suppression. The distortion also removes the degeneracy of zero eigenvalues. Depending on the correlation structures, interesting properties of the eigenvalue spectra are found. We simulate different correlated Wishart matrices to compare the results with empirical return matrices computed using the S&P 500 (USA) market data for the period 1985-2016. We also briefly review two recent applications of RMT in financial stock markets: (i) Identification of "market states" and long-term precursor to a critical state; (ii) Characterization of catastrophic instabilities (market crashes)., Comment: 22 pages, 12 figures. To appear in the Proceedings of Econophys-2017 and APEC-2017, New Delhi

The study of the critical dynamics in complex systems is always interesting yet challenging. Here, we choose financial market as an example of a complex system, and do a comparative analyses of two stock markets - the S&P 500 (USA) and Nikkei 225 (JPN). Our analyses are based on the evolution of crosscorrelation structure patterns of short time-epochs for a 32-year period (1985-2016). We identify "market states" as clusters of similar correlation structures, which occur more frequently than by pure chance (randomness). The dynamical transitions between the correlation structures reflect the evolution of the market states. Power mapping method from the random matrix theory is used to suppress the noise on correlation patterns, and an adaptation of the intra-cluster distance method is used to obtain the "optimum" number of market states. We find that the USA is characterized by four market states and JPN by five. We further analyze the co-occurrence of paired market states; the probability of remaining in the same state is much higher than the transition to a different state. The transitions to other states mainly occur among the immediately adjacent states, with a few rare intermittent transitions to the remote states. The state adjacent to the critical state (market crash) may serve as an indicator or a "precursor" for the critical state and this novel method of identifying the long-term precursors may be very helpful for constructing the early warning system in financial markets, as well as in other complex systems., Comment: 30 pages, 10 figures, including supplementary figures and information

We present a new model for the diffusion of innovation. Here, the population is segmented into distinct groups. Adoption by a particular group of some cultural product may be inhibited both by large numbers of its own members already having adopted but also, in particular, by members of another group having adopted. Intergroup migration is also permitted. We determine the equilibrium points and carry out stability analysis for the model for a two-group population. We also simulate a discrete time version of the model. Lastly, we present data on tablet use in eight countries from 2012-2016 and show that the relationship between use in the "under 25" age group and "55+" age group conforms to the model.

Terrorism instills fear in the minds of people and takes away the freedom of individuals to act as they will. Terrorism has turned out to be an international menace today. Here, we study the terrorist attack incidents which occurred in the last half-century across the globe from the open source, Global Terrorism Database, and develop a view on their spatio-temporal dynamics. We construct a complex network of global terrorism and study its growth dynamics, along with the statistical properties of the anti-social network, which are quite intriguing. Normally, each nation pursues its own vision of international security based upon its mandate and particular notions of politics and its policies to counter the threat of terrorism that could naturally include the use of tactical measures and strategic negotiations, or even physical power. We study the network resilience against targeted attacks and random failures, which could guide the counterterrorist outfits in designing strategies to fight terrorism. We then use a disparity filter method to isolate backbone of the network, and identify the terror hubs and vulnerable motifs of global terrorism. We also examine evolution of the hubs and motifs in a few exemplary cases like Afghanistan, Colombia, India, Israel, Pakistan and the United Kingdom. The dynamics of the terror hubs and the vulnerable motifs that we discover in the network backbone turn out to be very significant, and may provide deep insight on their formations and spreading, and thereby help in contending terrorism or framing public policies that can check their spread., Comment: 33 pages, 11 figures, 5 tables

Catastrophic events, though rare, do occur and when they occur, they have devastating effects. It is, therefore, of utmost importance to understand the complexity of the underlying dynamics and signatures of catastrophic events, such as market crashes. For deeper understanding, we choose the US and Japanese markets from 1985 onward, and study the evolution of the cross-correlation structures of stock return matrices and their eigenspectra over different short time-intervals or "epochs". A slight non-linear distortion is applied to the correlation matrix computed for any epoch, leading to the emerging spectrum of eigenvalues. The statistical properties of the emerging spectrum display: (i) the shape of the emerging spectrum reflects the market instability, (ii) the smallest eigenvalue may be able to statistically distinguish the nature of a market turbulence or crisis -- internal instability or external shock, and (iii) the time-lagged smallest eigenvalue has a statistically significant correlation with the mean market cross-correlation. The smallest eigenvalue seems to indicate that the financial market has become more turbulent in a similar way as the mean does. Yet we show features of the smallest eigenvalue of the emerging spectrum that distinguish different types of market instabilities related to internal or external causes. Based on the paradigmatic character of financial time series for other complex systems, the capacity of the emerging spectrum to understand the nature of instability may be a new feature, which can be broadly applied., Comment: 17 pages, 4 figures

A society or country with income equally distributed among its people is truly a fiction! The phenomena of socioeconomic inequalities have been plaguing mankind from times immemorial. We are interested in gaining an insight about the co-evolution of the countries in the inequality space, from a data science perspective. For this purpose, we use the time series data for Gini indices of different countries, and construct the equal-time cross-correlation matrix. We then use this to construct a similarity matrix and generate a map with the countries as different points generated through a multi-dimensional scaling technique. We also produce a similar map of different countries using the time series data for Gross Domestic Savings (% of GDP). We also pose a different, yet significant, question: Can higher savings moderate the income inequality? In this paper, we have tried to address this question through another data science technique - linear regression, to seek an empirical linkage between the income inequality and savings, mainly for relatively small or closed economies. This question was inspired from an existing theoretical model proposed by Chakraborti-Chakrabarti (2000), based on the principle of kinetic theory of gases. We tested our model empirically using Gini index and Gross Domestic Savings, and observed that the model holds reasonably true for many economies of the world., Comment: 8 pages, 6 figures. IEEE format. Accepted for publication in 5th IEEE DSAA 2018 conference at Torino, Italy

In this article, we present a brief narration of the origin and the overview of the recent developments done on the Kolkata Paise Restaurant (KPR) problem, which can serve as a prototype for a broader class of resource allocation problems in the presence of a large number of competing agents, typically studied using coordination and anti-coordination games. We discuss the KPR and its several extensions, as well as its applications in many economic and social phenomena. We end the article with some discussions on our ongoing experimental analysis of the same problem. We demonstrate that this provides an interesting picture of how people analyze complex situations, and design their strategies or react to them., Comment: 14 pages, Submitted for publication in a special issue in Science and Culture (Kolkata, India)

News reports in media contain records of a wide range of socio-economic and political events in time. Using a publicly available, large digital database of news records, and aggregating them over time, we study the network of ethnic conflicts and human rights violations. Complex network analyses of the events and the involved actors provide important insights on the engaging actors, groups, establishments and sometimes nations, pointing at their long range effect over space and time. We find power law decays in distributions of actor mentions, co-actor mentions and degrees and dominance of influential actors and groups. Most influential actors or groups form a giant connected component which grows in time, and is expected to encompass all actors globally in the long run. We demonstrate how targeted removal of actors may help stop spreading unruly events. We study the cause-effect relation between types of events, and our quantitative analysis confirm that ethnic conflicts lead to human rights violations, while it does not support the converse., Comment: 16 pages; main paper + Supplementary Information file; accepted for publication in Scientific Reports

In the framework of complexity theory, which provides a unified framework for natural and social sciences, we study the complex and interesting problem of the internal structure, similarities, and differences between the Mazatec dialects, an endangered Otomanguean language spoken in south-east Mexico. The analysis is based on some databases, which are used to compute linguistic distances between the dialects. The results are interpreted in the light of linguistics as well as statistical considerations and used to infer the history of the development of the observed pattern of diversity., Comment: 23 pages, 9 figures. A similar version was submitted to the Proceedings of Econophys-2015 to be published in "Econophysics and Sociophysics: Recent Progress and Future Directions" Editors: Abergel, F., Aoyama, H., Chakrabarti, B.K., Chakraborti, A., Deo, N., Raina, D., Vodenska, I

A brief overview of the models and data analyses of income, wealth, consumption distributions by the physicists, are presented here. It has been found empirically that the distributions of income and wealth possess fairly robust features, like the bulk of both the income and wealth distributions seem to reasonably fit both the log-normal and Gamma distributions, while the tail of the distribution fits well to a power law (as first observed by sociologist Pareto). We also present our recent studies of the unit-level expenditure on consumption across multiple countries and multiple years, where it was found that there exist invariant features of consumption distribution: the bulk is log-normally distributed, followed by a power law tail at the limit. The mechanisms leading to such inequalities and invariant features for the distributions of socio-economic variables are not well-understood. We also present some simple models from physics and demonstrate how they can be used to explain some of these findings and their consequences., Comment: 19 pages, 6 figures. Springer-Verlag format. Lecture note based on the seminars delivered at International Christian University-Mitaka, Japan, Indian Institute of Advanced Study (IIAS)-Shimla, India and Asian Development Research Institute-Patna, India

In the light of contemporary discussions of inter and transdisciplinarity, this paper approaches econophysics and sociophysics to seek a response to the question -- whether these interdisciplinary fields could contribute to physics and economics. Drawing upon the literature on history and philosophy of science, the paper argues that the two way traffic between physics and economics has a long history and this is likely to continue in the future., Comment: 9 pages, EPJ format. To appear in the European Physical Journal Special Topics, entitled "Can economics be a physical science?" Eds. A.S. Chakrabarti et al

We study unit-level expenditure on consumption across multiple countries and multiple years, in order to extract invariant features of consumption distribution. We show that the bulk of it is lognormally distributed, followed by a power law tail at the limit. The distributions coincide with each other under normalization by mean expenditure and log scaling even though the data is sampled across multiple dimension including, e.g., time, social structure and locations. This phenomenon indicates that the dispersions in consumption expenditure across various social and economic groups are significantly similar subject to suitable scaling and normalization. Further, the results provide a measurement of the core distributional features. Other descriptive factors including those of sociological, demographic and political nature, add further layers of variation on the this core distribution. We present a stochastic multiplicative model to quantitatively characterize the invariance and the distributional features.

We study the distributional features and inequality of consumption expenditure across India, for different states, castes, religion and urban-rural divide. We find that even though the aggregate measures of inequality are fairly diversified across states, the consumption distributions show near identical statistics, once properly normalized. This feature is seen to be robust with respect to variations in sociological and economic factors. We also show that state-wise inequality seems to be positively correlated with growth which is in accord with the traditional idea of Kuznets' curve. We present a brief model to account for the invariance found empirically and show that better but riskier technology draws can create a positive correlation between inequality and growth., Comment: 14 pages, 5 figs, 4 tables; Accepted in Physica A

In this article, we briefly review the different aspects and applications of kinetic exchange models in economics and sociology. Our main aim is to show in what manner the kinetic exchange models for closed economic systems were inspired by the kinetic theory of gas molecules. The simple yet powerful framework of kinetic theory, first proposed in 1738, led to the successful development of statistical physics of gases towards the end of the 19th century. This framework was successfully adapted to modeling of wealth distributions in the early 2000's. In later times, it was applied to other areas like firm dynamics and opinion formation in the society, as well. We have tried to present the flavour of the several models proposed and their applications, intentionally leaving out the intricate mathematical and technical details., Comment: 19 pages, 3 figures. To appear in Eds. R. Lopez-Ruiz, D. Fournier-Prunaret, Y. Nishio, C. Gracio, Nonlinear Maps and their Applications, Springer Proceedings in Mathematics & Statistics

In this paper, we investigate the dynamical properties of a psychological uplift in lovers. We first evaluate extensively the dynamical equations which were recently given by Rinaldi et. al., Physica A 392, pp.3231-3239 (2013). Then, the dependences of the equations on several parameters are numerically examined. From the view point of lasting partnership for lovers, especially, for married couples, one should optimize the parameters appearing in the dynamical equations to maintain the love for their respective partners. To achieve this optimization, we propose a new idea where the parameters are stochastic variables and the parameters in the next time step are given as expectations over a Boltzmann-Gibbs distribution at a finite temperature. This idea is very general and might be applicable to other models dealing with human relationships., Comment: 12 pages, 4 figures. To appear in Eds. R. Lopez-Ruiz, D. Fournier-Prunaret, Y. Nishio, C. Gracio, Nonlinear Maps and their Applications, Springer Proceedings in Mathematics & Statistics

Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines., Comment: 24 pages, 4 figures, review article; Accepted in Physics Reports

We discuss several multi-agent models that have their origin in the kinetic exchange theory of statistical mechanics and have been recently applied to a variety of problems in the social sciences. This class of models can be easily adapted for simulations in areas other than physics, such as the modeling of income and wealth distributions in economics and opinion dynamics in sociology., Comment: 7 pages, 4 figures, REVTeX format. Tutorial article to appear in the American Journal of Physics. Revised figures, corrected and added references

We propose a minimal multi-agent model for the collective dynamics of opinion formation in the society, by modifying kinetic exchange dynamics studied in the context of income, money or wealth distributions in a society. This model has an intriguing spontaneous symmetry breaking transition to polarized opinion state starting from non-polarized opinion state. In order to analyze the model, we introduce an iterative map version of the model, which has very similar statistical characteristics. An approximate theoretical analysis of the numerical results are also given, based on the iterative map version., Comment: 6 pages, 6 figures, REVTeX. Major revisions, analyses and explanations added

We propose a minimal model for the collective dynamics of opinion formation in the society, by modifying kinetic exchange dynamics studied in the context of income, money or wealth distributions in a society. This model has an intriguing spontaneous symmetry breaking transition., Comment: 4 pages REVTeX format, 2 figures. Revised version. To appear in "Econophysics", a special issue in Science and Culture (Kolkata, India) to celebrate 15 years of Econophysics

We review some aspects, especially those we can tackle analytically, of a minimal model of closed economy analogous to the kinetic theory model of ideal gases where the agents exchange wealth amongst themselves such that the total wealth is conserved, and each individual agent saves a fraction (0 < lambda < 1) of wealth before transaction. We are interested in the special case where the fraction lambda is constant for all the agents (global saving propensity) in the closed system. We show by moment calculations that the resulting wealth distribution cannot be the Gamma distribution that was conjectured in Phys. Rev. E 70, 016104 (2004). We also derive a form for the distribution at low wealth, which is a new result., Comment: 7 pages, 4 figures in REVTeX format. Revised version. To appear in "Econophysics", a special issue in Science and Culture (Kolkata, India) to celebrate 15 years of Econophysics

We discuss the equivalence between kinetic wealth-exchange models, in which agents exchange wealth during trades, and mechanical models of particles, exchanging energy during collisions. The universality of the underlying dynamics is shown both through a variational approach based on the minimization of the Boltzmann entropy and a complementary microscopic analysis of the collision dynamics of molecules in a gas. In various relevant cases the equilibrium distribution is the same for all these models, namely a gamma-distribution with suitably defined temperature and number of dimensions. This in turn allows one to quantify the inequalities observed in the wealth distributions and suggests that their origin should be traced back to very general underlying mechanisms: for instance, it follows that the smaller the fraction of the relevant quantity (e.g. wealth or energy) that agents can exchange during an interaction, the closer the corresponding equilibrium distribution is to a fair distribution., Comment: Presented to the International Workshop and Conference on: Statistical Physics Approaches to Multi-disciplinary Problems, January 07-13, 2008, IIT Guwahati, India

Prices of commodities or assets produce what is called time-series. Different kinds of financial time-series have been recorded and studied for decades. Nowadays, all transactions on a financial market are recorded, leading to a huge amount of data available, either for free in the Internet or commercially. Financial time-series analysis is of great interest to practitioners as well as to theoreticians, for making inferences and predictions. Furthermore, the stochastic uncertainties inherent in financial time-series and the theory needed to deal with them make the subject especially interesting not only to economists, but also to statisticians and physicists. While it would be a formidable task to make an exhaustive review on the topic, with this review we try to give a flavor of some of its aspects., Comment: 16 pages, 7 figures, submitted for publication in the Proceedings Volume of the International Workshop "Econophys-Kolkata III", Saha Institute of Nuclear Physics, March 12-15, 2007

We review the basic kinetic wealth-exchange models of Angle [J. Angle, Social Forces 65 (1986) 293; J. Math. Sociol. 26 (2002) 217], Bennati [E. Bennati, Rivista Internazionale di Scienze Economiche e Commerciali 35 (1988) 735], Chakraborti and Chakrabarti [A. Chakraborti, B. K. Chakrabarti, Eur. Phys. J. B 17 (2000) 167], and of Dragulescu and Yakovenko [A. Dragulescu, V. M. Yakovenko, Eur. Phys. J. B 17 (2000) 723]. Analytical fitting forms for the equilibrium wealth distributions are proposed. The influence of heterogeneity is investigated, the appearance of the fat tail in the wealth distribution and the relaxation to equilibrium are discussed. A unified reformulation of the models considered is suggested., Comment: Updated version; 9 pages, 5 figures, 2 tables

We review some statistical many-agent models of economic and social systems inspired by microscopic molecular models and discuss their stochastic interpretation. We apply these models to wealth exchange in economics and study how the relaxation process depends on the parameters of the system, in particular on the saving propensities that define and diversify the agent profiles., Comment: Revised final version. 6 pages, 5 figures

We present an outlook of the studies on correlations in the price timeseries of stocks, discussing the construction and applications of "asset tree". The topic discussed here should illustrate how the complex economic system (financial market) enrichens the list of existing dynamical systems that physicists have been studying for long., Comment: 6 pages, RevTeX format. To appear in the Conference Proceedings of ECONOPHYS-KOLKATA II: International Workshop on Econophysics of Stock Markets and Minority Games", February 14-17, 2006, SINP, Kolkata, as a book chapter in Eds. A. Chatterjee and B.K. Chakrabarti, Econophysics of Stock and other Markets, (Springer-Verlag (Italia), Milan, 2006)

Some general features of kinetic multi-agent models are reviewed, with particular attention to the relation between the agent saving propensities and the form of the equilibrium wealth distribution. The effect of a finite cutoff of the saving propensity distribution on the corresponding wealth distribution is studied. Various results about kinetic multi-agent models are collected and used to construct a realistic wealth distribution with zero limit for small values of wealth, an exponential form at intermediate and a power law tail at larger values of wealth., Comment: 9 pages, 6 figures. To be presented at the WEHIA 2005, University of Essex, United Kingdom on June 13-15, 2005

Various multi-agent models of wealth distributions defined by microscopic laws regulating the trades, with or without a saving criterion, are reviewed. We discuss and clarify the equilibrium properties of the model with constant global saving propensity, resulting in Gamma distributions, and their equivalence to the Maxwell-Boltzmann kinetic energy distribution for a system of molecules in an effective number of dimensions $D_\lambda$, related to the saving propensity $\lambda$ [M. Patriarca, A. Chakraborti, and K. Kaski, Phys. Rev. E 70 (2004) 016104]. We use these results to analyze the model in which the individual saving propensities of the agents are quenched random variables, and the tail of the equilibrium wealth distribution exhibits a Pareto law $f(x) \propto x^{-\alpha -1}$ with an exponent $\alpha=1$ [A. Chatterjee, B. K. Chakrabarti, and S. S. Manna, Physica Scripta T106 (2003) 367]. Here, we show that the observed Pareto power law can be explained as arising from the overlap of the Maxwell-Boltzmann distributions associated to the various agents, which reach an equilibrium state characterized by their individual Gamma distributions. We also consider the influence of different types of saving propensity distributions on the equilibrium state., Comment: 18 pages, 9 figures, Springer style. Submitted to the Proc. Vol. for the International Workshop on the "Econophysics of Wealth Distributions"

This paper introduces a new methodology for constructing a network of companies called a dynamic asset graph. This is similar to the dynamic asset tree studied recently, as both are based on correlations between asset returns. However, the new modified methodology does not, in general, lead to a tree but a graph, or several graphs that need not be inter-connected. The asset tree, due to the minimum spanning tree criterion, is forced to ``accept'' edge lengths that are far less optimal (longer) than the asset graph, thus resulting in higher overall length for the tree. The same criterion also causes asset trees to be more fragile in structure when measured by the single-step survival ratio. Over longer time periods, in the beginning the asset graph decays more slowly than the asset tree, but in the long-run the situation is reversed. The vertex degree distributions indicate that the possible scale free behavior of the asset graph is not as evident as it is in the case of the asset tree., Comment: 8 pages including 10 figures. Uses REVTeX. Submitted for the conference proceedings of "Unconventional Applications of Statistical Physics", Kolkata (2003)

The time dependence of the recently introduced minimum spanning tree description of correlations between stocks, called the ``asset tree'' have been studied to reflect the economic taxonomy. The nodes of the tree are identified with stocks and the distance between them is a unique function of the corresponding element of the correlation matrix. By using the concept of a central vertex, chosen as the most strongly connected node of the tree, an important characteristic is defined by the mean occupation layer (MOL). During crashes the strong global correlation in the market manifests itself by a low value of MOL. The tree seems to have a scale free structure where the scaling exponent of the degree distribution is different for `business as usual' and `crash' periods. The basic structure of the tree topology is very robust with respect to time. We also point out that the diversification aspect of portfolio optimization results in the fact that the assets of the classic Markowitz portfolio are always located on the outer leaves of the tree. Technical aspects like the window size dependence of the investigated quantities are also discussed., Comment: 13 pages including 12 figures. Uses REVTeX

The minimum spanning tree, based on the concept of ultrametricity, is constructed from the correlation matrix of stock returns. The dynamics of this asset tree can be characterised by its normalised length and the mean occupation layer, as measured from an appropriately chosen centre called the `central node'. We show how the tree length shrinks during a stock market crisis, Black Monday in this case, and how a strong reconfiguration takes place, resulting in topological shrinking of the tree., Comment: 6 pages, 3 eps figues. Elsevier style. Will appear in Physica A as part of the Bali conference proceedings, in press