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Green bonds are one of the most fascinating financial innovations that offer a solution to climate change and sustainable development from the financial point of view. In this study, we employ methods from statistical physics to examine the multifractal features of cross-correlations between green bonds and emerging stock markets. Utilizing multifractal detrended cross-correlation analysis (MFDCCA) on return and volatility series, our findings reveal significant cross-correlations between green bonds and emerging stock markets. The MFDCCA results uncover multifractal features and long-range cross-correlations between the two assets. Notably, volatility cross-correlations exhibit persistent behavior, while return cross-correlations vary across small and large fluctuation periods. These findings hold practical implications for policymakers and investors involved in green bonds and emerging stock markets. [ABSTRACT FROM AUTHOR]

The stock market operates on informed decisions based on information gathered from heterogeneous sources, encompassing diverse beliefs, strategies, and knowledge. This study examines the validity of rational bubbles in stock market prices, focusing on eight African stock markets: South Africa, Nigeria, Kenya, Egypt, Morocco, Mauritius, Ghana, and Botswana. Utilizing newly developed econophysics-based unit root tests and the Dynamic Conditional Correlation Multivariate Generalized Autoregressive Conditional Heteroskedasticity (DCC MGARCH) models, the authors analyzed daily data from 1996 to 2022. Our findings indicate that these markets experienced bubbles at various points, often followed by bursts. These bubbles coincided with significant economic changes, suggesting a strong link between stock market behavior and economic growth. For instance, financial crises, political instability, and global economic downturns significantly influenced bubble formation and bursts in these markets. The study reveals that market-specific events, such as regulatory changes and shifts in investor sentiment, also contributed to the occurrence of bubbles. Three key policy options are proposed to address bubbles in the studied markets including, enhancing regulatory frameworks to monitor and mitigate bubble formation, improving financial literacy among investors to promote informed decision-making, and strengthening economic policies to stabilize macroeconomic conditions and reduce vulnerability to external shocks. By implementing these measures, policymakers can enhance market stability and foster sustainable economic growth in African stock markets. [ABSTRACT FROM AUTHOR]

This paper leverages turbulence theory from physics to examine the similarities and differences between financial market volatility and turbulent phenomena on a statistical physics level. By drawing analogies between the dynamics of financial markets and fluid turbulence, an innovative analytical framework has been developed to enhance our understanding of the complexity inherent in financial markets. The research methodology involves a comparative analysis of several national stock market indices and simulated turbulent velocity time series, with a particular focus on key statistical properties such as probability distributions, correlation structures, and power spectral densities. Furthermore, a financial market capital flow model has been established, and corresponding solutions have been proposed. Through computational simulations and data analysis, it was discovered that financial market volatility shares some statistical characteristics with turbulence, yet there are significant differences in the shape of probability distributions and the timescales of correlations. This indicates that although financial markets exhibit patterns similar to turbulence, as a multivariate-driven complex system, their behavioral patterns do not completely correspond to natural turbulence phenomena, highlighting the limitations of directly applying turbulence theory to financial market analysis. Additionally, the study explores the use of Bézier curves to simulate market volatility and, based on these analyses, formulates trading strategies that demonstrate practical applications in risk management. This research provides fresh perspectives for the fields of financial market theory and econophysics, offering new insights into the complexity of financial markets and the prevention and management of financial risks. [ABSTRACT FROM AUTHOR]

AbstractThis article explores the evolution of the gravity model in international trade studies, emphasising systematic barriers to its acceptance. Employing a chronological and argumentative approach, it examines the emergence of the gravity concept, comparing Isard’s original contribution with Tinbergen’s econometric approach. It discusses how the heuristic nature of economics and a perceived lack of theoretical foundation initially hindered the gravity equation’s use. The works of Tinbergen’s contemporaries, including Linnemann and Anderson, are introduced. Lastly, recent findings in research will be reviewed, such as Krugman’s New Economic Geography, which seeks to encompass Isard’s intention to combine international trade with localisation theories. [ABSTRACT FROM AUTHOR]

Inclusively new to econophysics studies, herewith proposed techno-econophysics as part of techno-economy, econophysics & sociophysics to interparts description between probability and hypothesis evidently found between fractal realms and econophysics of markets, physics markets or stock markets any chaotic evidence [exergy destructive ] could present if effective & efficient criterion doesn’t complied. More precise iterative study ought to be held to configure how fractal dimension involved in techno-econophysics study of Helium Nat Gas Project which are not integer, but also proofed numerically & analytically. [ABSTRACT FROM AUTHOR]

While nature loves symmetry inasmuch as many natural laws remain invariant under various transformations, description of the natural diversity warrants some kind of breakdown of symmetry. Such a breakdown of symmetry may be either explicit or spontaneous. Many significant developments have taken place in recent times in diverse fields of study. Algorithmic information theory has been formulated by Kolmogorov and others. Spontaneous breakdown of symmetry and its use in the standard model of particle physics, discovery of the Higgs Boson are all notable events. Work of Ilya Prigogine to accommodate biological self-organisation within the ambit of the second law of thermodynamics is also quite noteworthy. According to some, his principle of minimum entropy production has added a dynamic content to the second law of thermodynamics, which otherwise is viewed as a mere kinematic constraint. It appears that non-linear dynamics and the catastrophe theory of Rene Thom can play an important role to understand a sudden qualitative change of a dynamical system triggered by certain value of a parameter. Phase change of water subjected to external heating or change from a stable economy to one marked by trade cycles are examples of such sudden transitions. Advent of econophysics and behavioural finance has facilitated a new way of looking logically at the problems of finance and economics with the help of established physical laws as well as rigorous mathematical and statistical analyses. Importance of such an approach is evident from the sad plight of Louis Bachelier. In this article, it has been our effort to link up such apparently disjoint developments from diverse fields of study within the ambit of a single logically consistent framework. [ABSTRACT FROM AUTHOR]

In addition to developing econophysical models that are, for example, those proposed in different publications [6-10], Econophysics also deals with the elaboration and study of new physical phenomena or technological processes for the development of different economic domains or industries. In this respect, the paper presents the theory and applications of the magneto-voltaic effect for obtaining electricity through unconventional and totally non-polluting technologies, without resorting to the use of hydrocarbon fuels or other technologies applied so far (wind, solar or hydroelectric energy) etc. [ABSTRACT FROM AUTHOR]

The Lillo–Mike–Farmer (LMF) model is an established econophysics model describing the order-splitting behaviour of institutional investors in financial markets. In the original article (Lillo et al. in Phys Rev E 71:066122, 2005), LMF assumed the homogeneity of the traders’ order-splitting strategy and derived a power-law asymptotic solution to the order-sign autocorrelation function (ACF) based on several heuristic reasonings. This report proposes a generalised LMF model by incorporating the heterogeneity of traders’ order-splitting behaviour that is exactly solved without heuristics. We find that the power-law exponent in the order-sign ACF is robust for arbitrary heterogeneous order-submission probability distributions. On the other hand, the prefactor in the ACF is very sensitive to heterogeneity in trading strategies and is shown to be systematically underestimated in the original homogeneous LMF model. Our work highlights that predicting the ACF prefactor is more challenging than the ACF exponent because many microscopic details (complex ingredients in actual data analyses) start to matter. [ABSTRACT FROM AUTHOR]

Mutually beneficial cooperation is a common part of economic systems as firms in partial cooperation with others can often make a higher sustainable profit. Though cooperative games were popular in 1950s, recent interest in noncooperative games is prevalent despite the fact that cooperative bargaining seems to be more useful in economic and political applications. In this paper we assume that the strategy space and time are inseparable with respect to a contract. Furthermore, it is assumed that each firm's strategy polygon is a geodesic polygon which changes its shape every point of time with the stubbornness strategy surface of firm's executive board follow a Gaussian free field. This gives us more flexibility to deal with generalized geodesic cooperative games which is the main contribution of this paper. Under this environment we show that the strategy spacetime is a dynamic curved Liouville-like 2-brane quantum gravity surface under asymmetric information and that traditional Euclidean geometry fails to give a proper feedback Nash equilibrium. Cooperation occurs when two firms' strategies fall into each other's influence curvature in this strategy spacetime. Small firms in an economy dominated by large firms are subject to the influence of large firms. We determine an optimal feedback semicooperation of the small firm in this case using a Liouville-Feynman path integral method. [ABSTRACT FROM AUTHOR]

This study derives space travel pricing by Walrasian Equilibrium, which is logical reasoning from the general relativity theory (GRT), the accounting equation, and economic supply and demand functions. The Cobb–Douglas functions embed the endogenous space factor as new capital to form the space travel firm's production function, which is also transformed into the consumer's utility function. Thus, the market equilibrium occurs at the equivalence of supply and demand functions, like the GRT, which presents the equivalence between the spatial geometric tensor and the energy–momentum tensor, explaining the principles of gravity and the motion of space matter in the spacetime framework. The mathematical axiomatic set theory of the accounting equation explains the equity premium effect that causes a short-term accounting equation inequality, then reaches the equivalence by suppliers' incremental equity through the closing accounts process of the accounting cycle. On the demand side, the consumption of space travel can be assumed as a value at risk (VaR) investment to attain the specific spacetime curvature in an expected orbit. Spacetime market equilibrium is then achieved to construct the space travel pricing model. The methodology of econophysics and the analogy method was applied to infer space travel pricing with the model of profit maximization, single-mindedness, and envy-free pricing in unit-demand markets. A case study with simulation was conducted for empirical verification of the mathematical models and algorithm. The results showed that space travel pricing remains associated with the principle of market equilibrium, but needs to be extended to the spacetime tensor of GRT. [ABSTRACT FROM AUTHOR]

Magazine Expansión publishes yearly its list of leading 500 top companies in Mexico. Its cumulative probability sales distribution per employee (per capita) exhibits a two-class structure: a quasi-Pareto power-law in the higher part and an exponential in the lower part which is qualitatively similar to income and wealth distributions in many countries of the world. Therefore, we posit that the income in wages and salaries of many Mexican workers is correlated to the sales revenue per employee of their corresponding employer firms. The relatively small number of state-owned enterprises (SOE) in this list is due to the privatization of most of the Mexican SOE during the past decades. [ABSTRACT FROM AUTHOR]

Green bonds represent a compelling financial innovation that presents a financial perspective solution to address climate change and promote sustainable development. On the other hand, the recent process of financialisation of commodities disrupts the dynamics of the commodity market, increasing its correlation with financial markets and raising the risks associated with commodities. In this context, understanding the dynamics of the interconnectivity between green bonds and commodity markets is crucial for risk management and portfolio diversification. This study aims to reveal the multifractal cross-correlations between green bonds and commodities by employing methods from statistical physics. We apply multifractal detrended cross-correlation analysis (MFDCCA) to both return and volatility series, demonstrating that green bonds and commodities exhibit multifractal characteristics. The analysis reveals long-range power-law cross-correlations between these two markets. Specifically, volatility cross-correlations persist across various fluctuations, while return series display persistence in small fluctuations and antipersistence in large fluctuations. These findings carry significant practical implications for hedging and risk diversification purposes. [ABSTRACT FROM AUTHOR]

Financial stress can have significant implications for individuals, businesses, asset prices and the economy as a whole. This study examines the nonlinear structure and dynamic changes in the multifractal behavior of cross-correlation between the financial stress index (FSI) and four well-known commodity indices, namely Commodity Research Bureau Index (CRBI), Baltic Dry Index (BDI), London Metal Index (LME) and Brent Oil prices (BROIL), using multifractal detrended cross correlation analysis (MFDCCA). For analysis, we utilized daily values of FSI and commodity index prices from 16 June 2016 to 9 July 2023. The following are the most important empirical findings: (I) All of the chosen commodity market indices show cross correlations with the FSI and have notable multifractal characteristics. (II) The presence of power law cross-correlation implies that a noteworthy shift in FSI is likely to coincide with a considerable shift in the commodity indices. (III) The multifractal cross-correlation is highest between FSI and Brent Oil (BROIL) and lowest with LME. (IV) The rolling windows analysis reveals a varying degree of persistency between FSI and commodity markets. The findings of this study have a number of important implications for commodity market investors and policymakers. [ABSTRACT FROM AUTHOR]

This study bridges finance and physics by applying thermodynamic concepts to model the limit order book (LOB) with high-frequency trading data on the Bitcoin spot. We derive the measures of Market Temperature and Market Entropy from the kinetic and potential energies in the LOB to provide a deeper understanding of order activities and market participant behavior. Market Temperature emerges as a robust indicator of market liquidity, correlating with liquidity measures such as Active Quote Volume, bid–ask spread and match volume. Market Entropy, on the other hand, quantifies the degree of disorder or randomness in the LOB, providing insights into the instantaneous volatility of price in the high-frequency trading market. Our empirical findings not only broaden the theoretical framework of econophysics but also enhance comprehensive understanding of the market microstructure and order book dynamics. [ABSTRACT FROM AUTHOR]

We present a novel reshuffling exchange model and investigate its long time behavior. In this model, two individuals are picked randomly, and their wealth X i and X j are redistributed by flipping a sequence of fair coins leading to a binomial distribution denoted B ∘ (X i + X j). This dynamics can be considered as a natural variant of the so-called uniform reshuffling model in econophysics. May refer to Cao, Jabin and Motsch (2023), Dragulescu and Yakovenko (2000). As the number of individuals goes to infinity, we derive its mean-field limit, which links the stochastic dynamics to a deterministic infinite system of ordinary differential equations. Our aim of this work is then to prove (using a coupling argument) that the distribution of wealth converges to the Poisson distribution in the 2 -Wasserstein metric. Numerical simulations illustrate the main result and suggest that the polynomial convergence decay might be further improved. [ABSTRACT FROM AUTHOR]

This document is an obituary announcing the passing of Professor Anca Gheorghiu, the President of the Hyperion University Senate. It describes her as a warm and generous person who was greatly loved by her students and colleagues. Professor Gheorghiu had a diverse educational background, with degrees in physics and economics, and she developed high-quality courses in both fields. She was also involved in volunteer work and had a talent for art. The document includes a condolences message from Professor F. V. Kusmartsev, highlighting Professor Gheorghiu's impact on the scientific community and her personal qualities. [Extracted from the article]

This (somewhat polemical) paper focuses on the ontological nature of money and draws comparisons to the ontological status of gauge freedom in physics. The parallels allow us to move beyond the social constructivist theories of Searle et al., and thereby avoid some pitfalls with such views. Since we have a reasonably good grasp of the ontological features in the physics context, we can pull back lessons from there onto the economic domain. In general, we find that this approach offers a nice lens through which to view the ontological peculiarities of money.

Purpose – The authors’ goal is to provide an overview and historical context for the various alternatives to the efficient market hypothesis (EMH) that have emerged over time. The authors found eight current alternatives that have emerged to address the EMH's flaws. Each of the proposed alternatives improves some of the assumptions made by the EMH, such as investor homogeneity, the immediate incorporation of information into asset values and the inadequacy of rationality to explain asset prices. Design/methodology/approach – To come up with the list of studies relevant to this review article, the authors used three databases, namely Scopus, Web of Science and Google Scholar. The first two were mostly used to get peer-reviewed articles while Google Scholar was used to extract articles that are still work in progress. The following words were used as the search queries; “efficient market hypothesis” and “alternatives to the efficient market hypothesis”. Findings – The alternatives to the EMH presented in this article demonstrate that market efficiency is a dynamic concept that can be best understood with a multidisciplinary approach. To better comprehend how financial markets work, it is crucial to draw on concepts, theories and ideas from a variety of disciplines, including physics, economics, anthropology, sociology and others. Originality/value – The authors comprehensively summarise the current state of the behavioural finance literature on alternatives to the EMH.

Pesticides are agricultural inputs that can significantly reduce yield losses, regulate plant growth, effectively liberate agricultural productivity, and improve food security. The availability of pesticides in economies worldwide is ensured by redistribution through international trade, with different economies playing different roles in this process. In this study, we measured and ranked the importance of economies using nine node metrics. We found that the clustering coefficient was negatively correlated with the other eight node metrics, whereas the other eight node metrics were positively correlated with each other and could be grouped into three communities (betweenness; in-degree, PageRank, authority, and in-closeness; out-degree, hub, and out-closeness). We further investigated the structural robustness of international pesticide trade networks proxied by large component size under three types of shocks to economies (node removal in descending, random, and ascending orders). The results showed that, except for the clustering coefficient, international pesticide trade networks are relatively robust under shocks to economies in ascending order but fragile under shocks to economies in descending order. By contrast, removing nodes with a clustering coefficient in ascending and descending order yielded similar robustness curves. Moreover, the structural robustness related to large component size evolved over time and exhibited an inverse U-shaped pattern.

The stock market operates on informed decisions based on information gathered from heterogeneous sources, encompassing diverse beliefs, strategies, and knowledge. This study examines the validity of rational bubbles in stock market prices, focusing on eight African stock markets: South Africa, Nigeria, Kenya, Egypt, Morocco, Mauritius, Ghana, and Botswana. Utilizing newly developed econophysics-based unit root tests and the Dynamic Conditional Correlation Multivariate Generalized Autoregressive Conditional Heteroskedasticity (DCC MGARCH) models, the authors analyzed daily data from 1996 to 2022. Our findings indicate that these markets experienced bubbles at various points, often followed by bursts. These bubbles coincided with significant economic changes, suggesting a strong link between stock market behavior and economic growth. For instance, financial crises, political instability, and global economic downturns significantly influenced bubble formation and bursts in these markets. The study reveals that market-specific events, such as regulatory changes and shifts in investor sentiment, also contributed to the occurrence of bubbles. Three key policy options are proposed to address bubbles in the studied markets including, enhancing regulatory frameworks to monitor and mitigate bubble formation, improving financial literacy among investors to promote informed decision-making, and strengthening economic policies to stabilize macroeconomic conditions and reduce vulnerability to external shocks. By implementing these measures, policymakers can enhance market stability and foster sustainable economic growth in African stock markets.

The COVID-19 pandemic has had an unprecedented impact on the global economy and financial markets. In this article, we explore the impact of the pandemic on the weak-form efficiency of the cryptocurrency and forex markets by conducting a comprehensive comparative analysis of the two markets. To estimate the weak-form of market efficiency, we utilize the asymmetric market deficiency measure (MDM) derived using the asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) approach, along with fuzzy entropy, Tsallis entropy, and Fisher information. Initially, we analyze the temporal evolution of these four measures using overlapping sliding windows. Subsequently, we assess both the mean value and variance of the distribution for each measure and currency in two distinct time periods: before and during the pandemic. Our findings reveal distinct shifts in efficiency before and during the COVID-19 pandemic. Specifically, there was a clear increase in the weak-form inefficiency of traditional currencies during the pandemic. Among cryptocurrencies, BTC stands out for its behavior, which resembles that of traditional currencies. Moreover, our results underscore the significant impact of COVID-19 on weak-form market efficiency during both upward and downward market movements. These findings could be useful for investors, portfolio managers, and policy makers. [ABSTRACT FROM AUTHOR]

This article is a theoretical development of the gravitational model through an econophysical approach and physical tools. Therefore, this paper attempts to answer the following research question: "Can physics still contribute to the development of the gravitational model in economics?". To tackle the question, this paper begins with an overview of the basic concepts of Newton's universal gravitational theory, which was first applied in economics by the distinguished American scientist Isard (1954). Then the concepts and formulas of gravitational fields in physics will be translated into economics, thus reviving Isard's original multilateralism through the elaboration of an extension of his model apt to describe the multilateralism and multi-country exchanges which characterize international trade. In this regard, the superposition principle of vector is used to offer vector analysis as a tool for mapping the interactions between the economic forces produced by the individual gravitational fields of different countries. A representation of the gravitational field of the European market will be provided. The field concept will extend the analysis from bilateral flows to the analysis of markets in two dimensions. [ABSTRACT FROM AUTHOR]

This study presents an econophysics based approach to the study of lotteries. By treating lotteries as complex systems we analyse the guiding dynamics of real-world lotteries. We found that the growth of the jackpot, that can be won, between two successive draws is proportional to its preceding value. This growth is best described as a linear function with two parameters a and b reflecting foundational player pool sales and the excitement generated by the current jackpot respectively. A computer simulation considering additional parameters (such as the price of a ticket: s, and the format of the lottery: p) is used to study the statistical features of simulated lotteries covering a vast parameter space. This approach enables us to construct a detailed map of how various parameters influence lottery behaviour by examining the statistical characteristics of the simulated lotteries. The findings emphasize the need for thoughtful pricing strategies in real-world lotteries and suggest that simulations can assist organizers in making informed decisions. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to perform Shariah review of Brownian motion that is used for prediction of Islamic stock prices and their volatility. Design/methodology/approach: It uses the Shariah compliant development model guidelines to review the Brownian motion and its applications. Findings: The model of Brownian motion does not involve any variable that renders it non-Shariah compliant; neither all applications of Brownian motion are Shariah compliant. Because the model is based on stochastic properties that involve randomness, therefore the issue of gharar takes the utmost important to handle in the applications of the model. The results need to be analyzed strictly in accordance with the Shariah whether they create any element of gharar or uncertainty in case of expected price and volatility estimates. Research limitations/implications: The research suffers from the limitation that it analyses only one model of physics, i.e. Brownian motion model from Shariah perspective. Practical implications: The research opens an area for Shariah analysis of results generated from the application of advanced models of physics on matters related to Islamic financial markets. Originality/value: The originality of this study stems from the fact that to the best of the authors' knowledge, it is the first study that extends Shariah guidelines into Financial physics for making the foundations of Islamic econophysics. [ABSTRACT FROM AUTHOR]

The importance of fertilizers to agricultural production is undeniable, and most economies rely on international trade for fertilizer use. The stability of fertilizer trade networks is fundamental to food security. However, quantifying the temporal stability of a fast-growing system, such as the international fertilizer trade, requires a multi-dimensional perception. Therefore, we propose a new method, namely the structural inheritance index, to distinguish the stability of the existing structure from the influence of the growing process. The well-known mutual information and Jaccard index are calculated for comparison. We use the three methods to measure the temporal stability of the overall network and different functional sub-networks of the three fertilizer nutrients N, P and K from 1990 to 2018. The international N, P and K trade systems all have a trend of increasing stability with the process of globalization. The existing structure in the fertilizer trading system has shown high stability since 1990, implying that the instability calculated by the Jaccard index in the early stage comes from the emergence of new trade. The stability of the K trade network is concentrated in large sub-networks, meaning that it is vulnerable to extreme events. The stable medium sub-network helps the N trade become the most stable nutrient trade. The P trade is clearly in the role of a catch-up player. Based on the analysis of the comparisons of three indicators, we concluded that all three nutrient trade networks enter a steady state. [ABSTRACT FROM AUTHOR]

In this paper we offer a comprehensive review of Sociophysics, focusing on relevant models as well as selected applications in social trading, behavioral finance and business. We discuss three key aspects of social diffusion dynamics, namely Opinion Dynamics (OD), Group Decision-Making (GDM) and Knowledge Dynamics (KD). In the OD case, we highlight special classes of social agents, such as informed agents, contrarians and extremists. As regards GDM, we present state-of-the-art models on various kinds of decision-making processes. In the KD case, we discuss processes of knowledge diffusion and creation via the presence of self-innovating agents. The primary question we wish to address is: to what extent does Sociophysics correspond to social reality? For that purpose, for each social diffusion model category, we present notable Sociophysics applications for real-world socioeconomic phenomena and, additionally, we provide a much-needed critique of the existing Sociophysics literature, so as to raise awareness of certain issues that currently undermine the effective application of Sociophysics, mainly in terms of modelling assumptions and mathematical formulation, on the investigation of key social processes.

In the article from the point of view of the system, energy and econophysic approaches, certain aspects of the theory and practice of measuring the effectivity (in particular, efficiency, performance) of the processes of functioning of the system are outlined. It is emphasized that modern realities point to the actualization of issues in quantum econophysics, in particular the adaptation and use of the mathematical apparatus of quantum mechanics for modeling processes in the economy, the use of quantum mechanical models and analogies, the application of quantum mechanical ideology, since modern socio-ecological-economic systems are complex, nonlinear, synergistic phenomena are observed in their dynamics, instability and poor predictability occur. The aim of the publication is to highlight some analogues of concepts and indicators similar to fundamental physical concepts in the paradigm of «cognition – measurement – evaluation – management» regarding the functioning of socio-ecological-economic systems and processes in them along with outlining approaches to determining the performance of these processes on the basis of modeling using the system, energy and econophysic approaches. It is proposed in the paradigm of «cognition – measurement – evaluation – management» regarding the performance of the processes of functioning of systems to take into account the economic interpretation of the Heisenberg uncertainty principle and the concept of the economic analogue of the Planck constant. It is substantiated that the theoretical and methodological analysis of some basic fundamental physical concepts (energy, momentum, etc.) and their formal and informal connections with real economic concepts and processes will contribute to the improvement of the procedure for determining and applying the energy efficiency coefficient of the processes of functioning of systems based on the authors’ indicators of the components of the performance of processes, taking into account the economic interpretation of the Heisenberg uncertainty principle and the concept of an economic analogue of the Planck constant.

This study aims to develop appropriate models for income distribution in Iran using the econophysics approach for the 2006–2018 period. For this purpose, the three improved distributions of the Pareto, Lognormal, and Gibbs-Boltzmann distributions are analyzed with the data extracted from the target household income expansion plan of the statistical centers in Iran. The research results indicate that the income distribution in Iran does not follow the Pareto and Lognormal distributions in most of the study years but follows the generalized Gibbs-Boltzmann distribution function in all study years. According to the results, the generalized Gibbs-Boltzmann distribution also properly fits the actual data distribution and could clearly explain the income distribution in Iran. The generalized Gibbs-Boltzmann distribution also fits the actual income data better than both Pareto and Lognormal distributions.

The aim of this paper is to use a special type of Einstein warped product manifolds recently introduced, the so-called PNDP-manifolds, for the differential geometric study, by focusing on some aspects related to dark field in financial market such as the concept of dark volatility. This volatility is not fixed in any relevant economic parameter, a sort of negative dimension, a ghost field, that greatly influences the behavior of real market. Since the PNDP-manifold has a "virtual" dimension, we want to use it in order to show how the Global Market is influenced by dark volatility, and in this regard we also provide an example, by considering the classical exponential models as possible solutions to our approach. We show how dark volatility, combined with specific conditions, leads to the collapse of a forward price.

The statistical properties of the international trade networks of all commodities as a whole have been extensively studied. However, the international trade networks of individual commodities often behave differently. Due to the importance of pesticides in agricultural production and food security, we investigated the evolving community structure in the international pesticide trade networks (iPTNs) of five categories from 2007 to 2018. We reveal that the community structures in the undirected and directed iPTNs exhibit regional patterns. However, the regional patterns are very different for undirected and directed networks and for different categories of pesticides. Moreover, the community structure is more stable in the directed iPTNs than in the undirected iPTNs. We also extract the intrinsic community blocks for the directed international trade networks of each pesticide category. It is found that the largest intrinsic community block is the most stable, appears in every pesticide category, and contains important economies (Belgium, Germany, Spain, France, the United Kingdom, Italy, the Netherlands, and Portugal) in Europe. Other important and stable intrinsic community blocks are Canada and the United States in North America, Argentina and Brazil in South America, and Australia and New Zealand in Oceania. These results suggest that, in the international trade of pesticides, geographic distance and the complementarity of important and adjacent economies are significant factors.

We investigate the unbiased model for money exchanges with collective debt limit: agents give at random time a dollar to one another as long as they have at least one dollar or they can borrow a dollar from a central bank if the bank is not empty. Surprisingly, this dynamic eventually leads to an asymmetric Laplace distribution of wealth (conjectured in [N. Xi, N. Ding, and Y. Wang, Phys. A, 357 (2005), pp. 543--555] and shown formally in a recent work [N. Lanchier and S. Reed, J. Stat. Phys., 176 (2019), pp. 1115--1137]). In this manuscript, we carry out a formal mean-field limit as the number of agents goes to infinity where we uncover a two-phase ODE dynamic. Convergence towards the unique equilibrium (two-sided geometric) distribution in the large time limit is also shown and the role played by the bank and debt (in terms of Gini index or wealth inequality) will be explored numerically as well. [ABSTRACT FROM AUTHOR]

Extreme inequality represents a grave challenge for impoverished individuals and poses a threat to economic growth and stability. Despite the fulfillment of affirmative action measures aimed at promoting equal opportunities, they often prove inadequate in effectively reducing inequality. Mathematical models and simulations have demonstrated that even when equal opportunities are present, wealth tends to concentrate in the hands of a privileged few, leaving the majority of the population in dire poverty. This phenomenon, known as condensation, has been shown to be an inevitable outcome in economic models that rely on fair exchange. In light of the escalating levels of inequality in the 21st century and the significant state intervention necessitated by the recent COVID-19 pandemic, an increasing number of scholars are abandoning neo-liberal ideologies. Instead, they propose a more robust role for the state in the economy, utilizing mechanisms such as taxation, regulation, and universal allocations. This paper begins with the assumption that state intervention is essential to effectively reduce inequality and to revitalize the economy. Subsequently, it conducts a comparative analysis of various taxation and redistribution mechanisms, with a particular emphasis on their impact on inequality indices, including the Gini coefficient. Specifically, it compares the effects of fortune and consumption-based taxation, as well as universal redistribution mechanisms or targeted redistribution mechanisms aimed at assisting the most economically disadvantaged individuals. The results suggest that fortune taxation are more effective than consumption-based taxation to reduce inequality. [ABSTRACT FROM AUTHOR]

Identifying macroeconomic events that are responsible for dramatic changes of economy is of particular relevance to understanding the overall economic dynamics. We introduce an open-source available efficient Python implementation of a Bayesian multi-trend change point analysis, which solves significant memory and computing time limitations to extract crisis information from a correlation metric. Therefore, we focus on the recently investigated S&P500 mean market correlation in a period of roughly 20 years that includes the dot-com bubble, the global financial crisis, and the Euro crisis. The analysis is performed two-fold: first, in retrospect on the whole dataset and second, in an online adaptive manner in pre-crisis segments. The online sensitivity horizon is roughly determined to be 80 up to 100 trading days after a crisis onset. A detailed comparison to global economic events supports the interpretation of the mean market correlation as an informative macroeconomic measure by a rather good agreement of change point distributions and major crisis events. Furthermore, the results hint at the importance of the U.S. housing bubble as a trigger of the global financial crisis, provide new evidence for the general reasoning of locally (meta)stable economic states, and could work as a comparative impact rating of specific economic events. [ABSTRACT FROM AUTHOR]

The analysis of market correlations is crucial for optimal portfolio selection of correlated assets, but their memory effects have often been neglected. In this work, we analyse the mean market correlation of the S&P500, which corresponds to the main market mode in principle component analysis. We fit a generalised Langevin equation (GLE) to the data whose memory kernel implies that there is a significant memory effect in the market correlation ranging back at least three trading weeks. The memory kernel improves the forecasting accuracy of the GLE compared to models without memory and hence, such a memory effect has to be taken into account for optimal portfolio selection to minimise risk or for predicting future correlations. Moreover, a Bayesian resilience estimation provides further evidence for non-Markovianity in the data and suggests the existence of a hidden slow time scale that operates on much slower times than the observed daily market data. Assuming that such a slow time scale exists, our work supports previous research on the existence of locally stable market states. [ABSTRACT FROM AUTHOR]

Dynamic pricing depends on the understanding of uncertain demand. We ask the question whether a stochastic system is sufficient to model this uncertainty. We propose a novel paradigm based on statistical analysis of recurrence quantification measures. The paradigm fits nonlinear dynamics by simultaneously optimizing both the determinism and the trapping time in recurrence plots and identifies an optimal time delay embedding. We firstly apply the paradigm on well-known deterministic and stochastic systems including Duffing systems and multi-fractional Gaussian noise. We then apply the paradigm to optimize the sampling of empirical point process data from RideAustin, a company providing ride share service in the city of Austin, Texas, the USA, thus reconstructing a period-7 attractor. Results show that in deterministic systems, an optimal embedding exists under which recurrence plots exhibit robust diagonal or vertical lines. However, in stochastic systems, an optimal embedding often does not exist, evidenced by the inability to shrink the standard deviation of either the determinism or the trapping time. By means of surrogate testing, we also show that a Poisson process or a stochastic system with periodic trend is insufficient to model uncertainty contained in empirical data. By contrast, the period-7 attractor dominates and well models nonlinear dynamics of empirical data via irregularly switching of the slow and the fast dynamics. Findings highlight the importance of fitting and recreating nonlinear dynamics of data in modeling practical problems. [ABSTRACT FROM AUTHOR]

The lattice gas automaton (LGA) is proposed for a closed economic market of agents with heterogeneous saving interests. There are two procedures in the standard LGA, i.e. "propagation" + "transaction". If the propagation step is removed and the transaction is conducted among all agents, the LGA reduces to a more simplified kinetic model. In addition, two dealing rules are imposed on the transaction phase. Under Rule I, the trading volume depends on the average saving propensities of an arbitrary pair of agents in trade. Under Rule II, the exchange is governed by a stochastic parameter between the saving propensities of two traders. Besides, two sampling methods are introduced for the random selection of two agents in the iterative process. Specifically, Sampling I is the sampling with replacement and is easier to program. Sampling II is the sampling without replacement and owns a higher computing efficiency. There are slight differences between the stationary wealth distributions simulated by using the two transaction rules and sampling approaches. In addition, the accuracy, robustness and efficiency of the econophysics models are validated by typical numerical tests. The reduced LGA without the propagation step owns a higher computational efficiency than the standard LGA. Moreover, the impact of saving propensities of agents in two groups on the wealth distributions is studied, and the influence of proportions of agents is investigated as well. To quantitatively measure the wealth inequality, the Gini coefficients, Kolkata indices, and deviation degrees of all agents and two groups are simulated and analyzed in detail. This work is helpful to further analyze and predict the dynamic process of wealth distribution in the realistic economic market. [ABSTRACT FROM AUTHOR]

Grains account for more than 50% of the calories consumed by people worldwide, and military conflicts, pandemics, climate change, and soaring grain prices all have vital impacts on food security. However, the complex price behavior of the global grain spot markets has not been well understood. A recent study performed multifractal moving average analysis (MF-DMA) of the Grains & Oilseeds Index (GOI) and its sub-indices of wheat, maize, soybeans, rice, and barley and it was found that only the maize and barley sub-indices exhibit an intrinsic multifractal nature with convincing evidence. Here, we utilize multifractal fluctuation analysis (MF-DFA) to investigate the same problem. Extensive statistical tests confirm the presence of intrinsic multifractality in the maize and barley sub-indices and the absence of intrinsic multifractality in the wheat and rice sub-indices. Different from the MF-DMA results, the MF-DFA results suggest that there is also intrinsic multifractality in the GOI and soybeans sub-indices. Our comparative analysis does not provide conclusive information about the GOI and soybeans and highlights the high complexity of the global grain spot markets. [ABSTRACT FROM AUTHOR]

The financial system, a complex network, operates primarily through the exchange of capital, where the role of information is critical. This study utilizes the transfer entropy method to examine the strength and direction of information flow among different capital flow time series and investigate the community structure within the transfer networks. Moreover, the spreading dynamics of the capital flow transfer networks are observed, and the importance and traveling time of each node are explored. The results imply a dominant role for the food and drink industry within the Chinese market, with increased attention towards the computer industry starting in 2014. The community structure of the capital flow transfer networks significantly differs from those constructed from stock prices, with the main sector predominantly encompassing industry leaders favored by primary funds with robust capital flow connections. The average traveling time from sectors such as food and drink, coal, and utilities to other sectors is the shortest, and the dynamic flow between these sectors displays a significant role. These findings highlight that comprehension of information flow and community structure within the financial system can offer valuable insights into market dynamics and help to identify key sectors and companies. [ABSTRACT FROM AUTHOR]

Prediction markets are heralded as powerful forecasting tools, but models that describe them often fail to capture the full complexity of the underlying mechanisms that drive price dynamics. To address this issue, we propose a model in which agents belong to a social network, have an opinion about the probability of a particular event to occur, and bet on the prediction market accordingly. Agents update their opinions about the event by interacting with their neighbours in the network, following the Deffuant model of opinion dynamics. Our results suggest that a simple market model that takes into account opinion formation dynamics is capable of replicating the empirical properties of historical prediction market time series, including volatility clustering and fat-tailed distribution of returns. Interestingly, the best results are obtained when there is the right level of variance in the opinions of agents. Moreover, this paper provides a new way to indirectly validate opinion dynamics models against real data by using historical data obtained from PredictIt, which is an exchange platform whose data have never been used before to validate models of opinion diffusion. [ABSTRACT FROM AUTHOR]

Increasing wealth inequality is a significant global issue that demands attention. While the distribution of wealth varies across countries based on their economic stages, there is a universal trend observed in the distribution function. Typically, regions with lower wealth values exhibit an exponential distribution, while regions with higher wealth values demonstrate a power-law distribution. In this review, we introduce measures that effectively capture wealth inequality and examine wealth distribution functions within the wealth exchange model. Drawing inspiration from the field of econophysics, wealth exchange resulting from economic activities is likened to a kinetic model, where molecules collide and exchange energy. Within this framework, two agents exchange a specific amount of wealth. As we delve into the analysis, we investigate the impact of various factors such as tax collection, debt allowance, and savings on the wealth distribution function when wealth is exchanged. These factors play a crucial role in shaping the dynamics of wealth distribution. [ABSTRACT FROM AUTHOR]

This study examines the response of the BRICS and MSCI emerging stock market indices to the COVID-19 outbreak. For this purpose, this study uses a multifractal detrended fluctuation analysis (MF-DFA) to investigate the market efficiency dynamics of these indices and then ranks them based on their market efficiency. Overall, our results indicate that the returns from all the stock indices exhibit long-range correlations, implying that these markets are not weak-form efficient. Specifically, China showed the highest level of multifractality (i.e., inefficiency), which can be attributed to its highly volatile market structure. Using a subsample analysis, we further explore the impact of COVID-19 on these markets' efficiency by dividing the dataset into pre- and post-COVID periods. The findings indicate that COVID-19 adversely affected the efficiency of all the indices. Surprisingly, improvement in the Chinese market's inefficiency was witnessed, which can be attributed to the prompt and effective measures (i.e., timely imposition of health-related measures such as lockdowns and resident quarantines to contain COVID-19 and financial packages designed to curtail the economic meltdown) introduced by the Chinese government. The findings of this study may help investors, policymakers and regulators in refining their financial and policy decisions according to the new efficiency levels of these markets. [ABSTRACT FROM AUTHOR]

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Institutional investors like hedge funds are particularly resilient in times of volatility, primarily due to their access to a slew of complex trading strategies and extensive research capabilities; both of which are generally outside the reach of common investors. Fortunately, the U.S. Securities and Exchange Commission has mandated that large institutional investors publicly disclose the positions held by them at the end of a quarter, within the following 45 days. We then ask the question "Given our access to snapshots of positions held by large investors, can we extract alpha by approximating their aggregate behaviour?" In this paper, we introduce a stock recommendation model driven by the aggregate behaviour of institutional investors. We interpret stocks as the states of a Markov chain. The corresponding state transition matrix is defined based on the aggregate behaviour of investors. By designing the transition matrix to hold for aperiodicity and irreducibility, the steady state distribution of this chain is treated as a ranked list of stocks. We build a long only, equally weighted portfolio of stocks to trade using these recommendations. We observe that the returns on this portfolio beat existing models in the literature, and standard hedge fund indices both in terms of annualised returns and Sharpe ratio. [ABSTRACT FROM AUTHOR]

Financial stress can have significant implications for individuals, businesses, asset prices and the economy as a whole. This study examines the nonlinear structure and dynamic changes in the multifractal behavior of cross-correlation between the financial stress index (FSI) and four well-known commodity indices, namely Commodity Research Bureau Index (CRBI), Baltic Dry Index (BDI), London Metal Index (LME) and Brent Oil prices (BROIL), using multifractal detrended cross correlation analysis (MFDCCA). For analysis, we utilized daily values of FSI and commodity index prices from 16 June 2016 to 9 July 2023. The following are the most important empirical findings: (I) All of the chosen commodity market indices show cross correlations with the FSI and have notable multifractal characteristics. (II) The presence of power law cross-correlation implies that a noteworthy shift in FSI is likely to coincide with a considerable shift in the commodity indices. (III) The multifractal cross-correlation is highest between FSI and Brent Oil (BROIL) and lowest with LME. (IV) The rolling windows analysis reveals a varying degree of persistency between FSI and commodity markets. The findings of this study have a number of important implications for commodity market investors and policymakers.

The global economy cannot be understood without the interaction of smaller-scale economies. We addressed this issue by considering a simplified economic model that still preserves the basic features, and analyzed the interaction of a set of such economies and the collective emerging dynamic. The topological structure of the economies' network appears to correlate with the collective properties observed. In particular, the strength of the coupling between the different networks as well as the specific connectivity of each node happen to play a crucial role in the determination of the final state. [ABSTRACT FROM AUTHOR]