Special Issue "Complexity in Economic and Social Systems"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: closed (31 August 2020).

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Stanisław Drożdż
E-Mail Website
Guest Editor
1. Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Kraków, Poland
2. Faculty of Computer Science and Telecommunications, Cracov University of Technology, 31-155 Kraków, Poland
Interests: complex systems; nuclear physics; quantum mechanics; multifractals; complex networks; nonlinear dynamics; deterministic chaos; random matrix theory; econophysics; quantitative linguistics
Dr. Jarosław Kwapień
E-Mail Website
Guest Editor
Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Kraków, Poland
Interests: complex systems; complex networks; financial markets; natural language; fractal analysis
Dr. Paweł Oświęcimka
E-Mail Website
Guest Editor
Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Kraków, Poland
Interests: fractals; multifractals; complex systems; time series analysis; econophysics

Special Issue Information

Dear Colleagues,

Whether complexity of a system is viewed in the purely intuitive sense of a nontrivial order that emerges spontaneously from an overall disorder or it is grasped more formally using one of several dozen mathematical, physical, and information-theoretic measures, we are surrounded by its signatures and face its manifestations almost everywhere. We are complex ourselves: We live in a society that is complex and we interact with others in a complex way. There is no exaggeration in a statement that our society is the most complex structure known to us in the universe. Social phenomena like the emergence of communication and cooperation, build-up of hierarchies and organizations, opinion formation, the emergence of political systems, and the structure and dynamics of financial markets are all among the iconic examples of the real-world complexity.

Specialists from such disciplines like mathematics, physics, information theory, and data science working together with econometrists, sociologists, quantitative linguists, and psychologists for more than a quarter century have already been dealing with such phenomena trying to describe them in a language of exact science, and to model and explain them using methods and tools that had earlier been applied successfully to natural systems. Although much has already been done and much has been achieved, the complexity of the social and economic systems is still far from being properly understood. This is why every possible effort and every meaningful contribution is welcome as it can bring us closer to the ultimate goal of understanding complexity both in reference to these systems in particular and as a physical phenomenon in general. It is also important to approach the problem from different angles by collecting many interdisciplinary works and views in one place like this Special Issue as human society eludes any narrow-scope, single-discipline analysis.

It thus becomes straightforward that we intend this Special Issue to cover a broad variety of complexity-related topics and methods in the following fields: macroeconomics, financial markets, epidemiology, opinion formation, social systems, quantitative linguistics, and time series analysis. We especially encourage to submit manuscripts that report studies carried out with models of heterogeneous interacting agents, complex networks, multifractal analysis, non-extensive statistical mechanics, and non-extensive entropy.

Prof. Dr. Stanisław Drożdż
Dr. Jarosław Kwapień
Dr. Paweł Oświęcimka
Guest Editors

Manuscript Submission Information

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Keywords

  • complexity
  • econophysics
  • sociophysics
  • quantitative linguistics
  • data science
  • time series analysis
  • multifractal analysis
  • non-extensive entropy
  • complex networks
  • social systems
  • financial markets
  • macroeconomics
  • epidemic spreading

Published Papers (24 papers)

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Editorial

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Editorial
Complexity in Economic and Social Systems
Entropy 2021, 23(2), 133; https://doi.org/10.3390/e23020133 - 21 Jan 2021
Cited by 1 | Viewed by 468
Abstract
During recent years we have witnessed a systematic progress in the understanding of complex systems, both in the case of particular systems that are classified into this group and, in general, as regards the phenomenon of complexity [...] Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)

Research

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Article
New Measure of Economic Development Based on the Four-Colour Theorem
Entropy 2021, 23(1), 61; https://doi.org/10.3390/e23010061 - 31 Dec 2020
Cited by 2 | Viewed by 679
Abstract
The location quotient is one of the basic quantitative tools for identifying the regional poles and the turnpikes of economic growth in spatial economy. The disadvantage of this traditional measure is the limited scope of economic information contained in it. The new measure [...] Read more.
The location quotient is one of the basic quantitative tools for identifying the regional poles and the turnpikes of economic growth in spatial economy. The disadvantage of this traditional measure is the limited scope of economic information contained in it. The new measure of economic development proposed in the article encompasses a complex spectrum of phenomena in one number, as it takes into account the influence of the public administration sector, as well as top technology in the form of ICT and its practical business models. It also takes into account the digital prosumption and the platforms for participation. The participation platforms in the public administration sector are the websites of municipal public administration offices. A cluster analysis was used to distinguish four quality classes of these websites. These classes were assigned four different colours, which were then used to draw up a map of the selected province. Each municipality is marked with a colour that corresponds to the quality class of the website of the state administration office operating on its territory. The colour system resulting from the four-colour theorem and the corresponding dual graph play the role of a reference system in relation to each empirical colour distribution and another dual graph related to it. The measure of the economic development of a region is the degree of reduction of the dual graph corresponding to the empirical distribution of colours, which identifies the actual growth poles and determines the routes of growth. The presented indicator better and more precisely identifies poles and routes of economic growth than the traditional location quotient. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
A Comprehensive Framework for Uncovering Non-Linearity and Chaos in Financial Markets: Empirical Evidence for Four Major Stock Market Indices
Entropy 2020, 22(12), 1435; https://doi.org/10.3390/e22121435 - 18 Dec 2020
Cited by 3 | Viewed by 826
Abstract
The presence of chaos in the financial markets has been the subject of a great number of studies, but the results have been contradictory and inconclusive. This research tests for the existence of nonlinear patterns and chaotic nature in four major stock market [...] Read more.
The presence of chaos in the financial markets has been the subject of a great number of studies, but the results have been contradictory and inconclusive. This research tests for the existence of nonlinear patterns and chaotic nature in four major stock market indices: namely Dow Jones Industrial Average, Ibex 35, Nasdaq-100 and Nikkei 225. To this end, a comprehensive framework has been adopted encompassing a wide range of techniques and the most suitable methods for the analysis of noisy time series. By using daily closing values from January 1992 to July 2013, this study employs twelve techniques and tools of which five are specific to detecting chaos. The findings show no clear evidence of chaos, suggesting that the behavior of financial markets is nonlinear and stochastic. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
The Value of Information Searching against Fake News
Entropy 2020, 22(12), 1368; https://doi.org/10.3390/e22121368 - 03 Dec 2020
Cited by 1 | Viewed by 745
Abstract
Inspired by the Daley-Kendall and Goffman-Newill models, we propose an Ignorant-Believer-Unbeliever rumor (or fake news) spreading model with the following characteristics: (i) a network contact between individuals that determines the spread of rumors; (ii) the value (cost versus benefit) for individuals who search [...] Read more.
Inspired by the Daley-Kendall and Goffman-Newill models, we propose an Ignorant-Believer-Unbeliever rumor (or fake news) spreading model with the following characteristics: (i) a network contact between individuals that determines the spread of rumors; (ii) the value (cost versus benefit) for individuals who search for truthful information (learning); (iii) an impact measure that assesses the risk of believing the rumor; (iv) an individual search strategy based on the probability that an individual searches for truthful information; (v) the population search strategy based on the proportion of individuals of the population who decide to search for truthful information; (vi) a payoff for the individuals that depends on the parameters of the model and the strategies of the individuals. Furthermore, we introduce evolutionary information search dynamics and study the dynamics of population search strategies. For each value of searching for information, we compute evolutionarily stable information (ESI) search strategies (occurring in non-cooperative environments), which are the attractors of the information search dynamics, and the optimal information (OI) search strategy (occurring in (eventually forced) cooperative environments) that maximizes the expected information payoff for the population. For rumors that are advantageous or harmful to the population (positive or negative impact), we show the existence of distinct scenarios that depend on the value of searching for truthful information. We fully discuss which evolutionarily stable information (ESI) search strategies and which optimal information (OI) search strategies eradicate (or not) the rumor and the corresponding expected payoffs. As a corollary of our results, a recommendation for legislators and policymakers who aim to eradicate harmful rumors is to make the search for truthful information free or rewarding. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
The Gender Productivity Gap in Croatian Science: Women Are Catching up with Males and Becoming Even Better
Entropy 2020, 22(11), 1217; https://doi.org/10.3390/e22111217 - 26 Oct 2020
Cited by 3 | Viewed by 1414
Abstract
How much different genders contribute to citations and whether we see different gender patterns between STEM and non-STEM researchers are questions that have long been studied in academia. Here we analyze the research output in terms of citations collected from the Web of [...] Read more.
How much different genders contribute to citations and whether we see different gender patterns between STEM and non-STEM researchers are questions that have long been studied in academia. Here we analyze the research output in terms of citations collected from the Web of Science of males and females from the largest Croatian university, University of Zagreb. Applying the Mann–Whitney statistical test, for most faculties, we demonstrate no gender difference in research output except for seven faculties, where males are significantly better than females on six faculties. We find that female STEM full professors are significantly more cited than male colleagues, while male non-STEM assistant professors are significantly more cited than their female colleagues. There are ten faculties where females have the larger average citations than their male colleagues and eleven faculties where the most cited researcher is woman. For the most cited researchers, our Zipf plot analyses demonstrate that both genders follow power laws, where the exponent calculated for male researchers is moderately larger than the exponent for females. The exponent for STEM citations is slightly larger than the exponent obtained for non-STEM citations, implying that compared to non-STEM, STEM research output leads to fatter tails and so larger citations inequality than non-STEM. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Innovativeness of Industrial Processing Enterprises and Conjunctural Movement
Entropy 2020, 22(10), 1177; https://doi.org/10.3390/e22101177 - 19 Oct 2020
Cited by 2 | Viewed by 778
Abstract
Singulation of components determining the innovative activity of enterprises is a complex issue as it depends on both microeconomic and macroeconomic factors. The purpose of this article is to present the results of research on the impact of the mutual interactions between ownership [...] Read more.
Singulation of components determining the innovative activity of enterprises is a complex issue as it depends on both microeconomic and macroeconomic factors. The purpose of this article is to present the results of research on the impact of the mutual interactions between ownership and the size of companies on the achievement of the objectives of innovative activity by Polish industrial processing enterprises in changing cyclical conditions. The importance of innovation barriers was also assessed. Empirical data came from three periods that covered different phases of the business cycle: prosperity 2004–2006, global financial crisis 2008–2010, and recovery 2012–2014. The research used a cybernetic approach based on feedback loops presenting interactions between variables. In addition, two statistical methods were used: the Pearson’s χ2 independence test and correspondence analysis. The following discoveries were made during the research: (1) consideration of the combined impact of ownership and the size of companies on their innovation activities makes it possible to study phenomena that may be overlooked if the impact of these factors is considered separately; (2) public enterprises achieve significantly worse results in terms of innovation than companies from other ownership sectors; (3) the Red Queen effect, which assumes that the best innovative enterprises exert selection pressure on all other companies, applies to industrial processing companies, and in particular public enterprises; (4) the industrial processing section is more sensitive to secular trends than to cyclical fluctuations; (5) confirmation of occurrence of the Polish Green Island effect, which assumes that companies achieve good results in terms of innovation, irrespective of the phases of the business cycle; and (6) statistical evidence is provided that the global financial crisis may be associated with the turn of the Fifth and Sixth Kondratieff waves. Most likely, the role of the communication channel between the world economy and the Polish manufacturing section is fulfilled by foreign ownership, whose percentage of share capital of this section is estimated at 50%. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
A Simple Mechanism Causing Wealth Concentration
Entropy 2020, 22(10), 1148; https://doi.org/10.3390/e22101148 - 13 Oct 2020
Cited by 3 | Viewed by 620
Abstract
We study mechanisms leading to wealth condensation. As a natural starting point, our model adopts a neoclassical point of view, i.e., we completely ignore work, production, and productive relations, and focus only on bilateral link between two randomly selected agents. We propose a [...] Read more.
We study mechanisms leading to wealth condensation. As a natural starting point, our model adopts a neoclassical point of view, i.e., we completely ignore work, production, and productive relations, and focus only on bilateral link between two randomly selected agents. We propose a simple matching process with deterministic trading rules and random selection of trading agents. Furthermore, we also neglect the internal characteristic of traded goods and analyse only the relative wealth changes of each agent. This is often the case in financial markets, where a traded good is money itself in various forms and various maturities. We assume that agents trade according to the rules of utility and decision theories. Agents possess incomplete knowledge about market conditions, but the market is in equilibrium. We show that these relatively frugal assumptions naturally lead to a wealth condensation. Moreover, we discuss the role of wealth redistribution in such a model. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Complexity in Economic and Social Systems: Cryptocurrency Market at around COVID-19
Entropy 2020, 22(9), 1043; https://doi.org/10.3390/e22091043 - 18 Sep 2020
Cited by 13 | Viewed by 2460
Abstract
Social systems are characterized by an enormous network of connections and factors that can influence the structure and dynamics of these systems. Among them the whole economical sphere of human activity seems to be the most interrelated and complex. All financial markets, including [...] Read more.
Social systems are characterized by an enormous network of connections and factors that can influence the structure and dynamics of these systems. Among them the whole economical sphere of human activity seems to be the most interrelated and complex. All financial markets, including the youngest one, the cryptocurrency market, belong to this sphere. The complexity of the cryptocurrency market can be studied from different perspectives. First, the dynamics of the cryptocurrency exchange rates to other cryptocurrencies and fiat currencies can be studied and quantified by means of multifractal formalism. Second, coupling and decoupling of the cryptocurrencies and the conventional assets can be investigated with the advanced cross-correlation analyses based on fractal analysis. Third, an internal structure of the cryptocurrency market can also be a subject of analysis that exploits, for example, a network representation of the market. In this work, we approach the subject from all three perspectives based on data from a recent time interval between January 2019 and June 2020. This period includes the peculiar time of the Covid-19 pandemic; therefore, we pay particular attention to this event and investigate how strong its impact on the structure and dynamics of the market was. Besides, the studied data covers a few other significant events like double bull and bear phases in 2019. We show that, throughout the considered interval, the exchange rate returns were multifractal with intermittent signatures of bifractality that can be associated with the most volatile periods of the market dynamics like a bull market onset in April 2019 and the Covid-19 outburst in March 2020. The topology of a minimal spanning tree representation of the market also used to alter during these events from a distributed type without any dominant node to a highly centralized type with a dominating hub of USDT. However, the MST topology during the pandemic differs in some details from other volatile periods. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Towards a Universal Measure of Complexity
Entropy 2020, 22(8), 866; https://doi.org/10.3390/e22080866 - 06 Aug 2020
Cited by 2 | Viewed by 992
Abstract
Recently, it has been argued that entropy can be a direct measure of complexity, where the smaller value of entropy indicates lower system complexity, while its larger value indicates higher system complexity. We dispute this view and propose a universal measure of complexity [...] Read more.
Recently, it has been argued that entropy can be a direct measure of complexity, where the smaller value of entropy indicates lower system complexity, while its larger value indicates higher system complexity. We dispute this view and propose a universal measure of complexity that is based on Gell-Mann’s view of complexity. Our universal measure of complexity is based on a non-linear transformation of time-dependent entropy, where the system state with the highest complexity is the most distant from all the states of the system of lesser or no complexity. We have shown that the most complex is the optimally mixed state consisting of pure states, i.e., of the most regular and most disordered which the space of states of a given system allows. A parsimonious paradigmatic example of the simplest system with a small and a large number of degrees of freedom is shown to support this methodology. Several important features of this universal measure are pointed out, especially its flexibility (i.e., its openness to extensions), suitability to the analysis of system critical behaviour, and suitability to study the dynamic complexity. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Looking at Extremes without Going to Extremes: A New Self-Exciting Probability Model for Extreme Losses in Financial Markets
Entropy 2020, 22(7), 789; https://doi.org/10.3390/e22070789 - 20 Jul 2020
Cited by 3 | Viewed by 1221
Abstract
Forecasting market risk lies at the core of modern empirical finance. We propose a new self-exciting probability peaks-over-threshold (SEP-POT) model for forecasting the extreme loss probability and the value at risk. The model draws from the point-process approach to the POT methodology but [...] Read more.
Forecasting market risk lies at the core of modern empirical finance. We propose a new self-exciting probability peaks-over-threshold (SEP-POT) model for forecasting the extreme loss probability and the value at risk. The model draws from the point-process approach to the POT methodology but is built under a discrete-time framework. Thus, time is treated as an integer value and the days of extreme loss could occur upon a sequence of indivisible time units. The SEP-POT model can capture the self-exciting nature of extreme event arrival, and hence, the strong clustering of large drops in financial prices. The triggering effect of recent events on the probability of extreme losses is specified using a discrete weighting function based on the at-zero-truncated Negative Binomial (NegBin) distribution. The serial correlation in the magnitudes of extreme losses is also taken into consideration using the generalized Pareto distribution enriched with the time-varying scale parameter. In this way, recent events affect the size of extreme losses more than distant events. The accuracy of SEP-POT value at risk (VaR) forecasts is backtested on seven stock indexes and three currency pairs and is compared with existing well-recognized methods. The results remain in favor of our model, showing that it constitutes a real alternative for forecasting extreme quantiles of financial returns. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Do Liquidity Proxies Based on Daily Prices and Quotes Really Measure Liquidity?
Entropy 2020, 22(7), 783; https://doi.org/10.3390/e22070783 - 17 Jul 2020
Cited by 2 | Viewed by 1288
Abstract
This paper examines whether liquidity proxies based on different daily prices and quotes approximate latent liquidity. We compare percent-cost daily liquidity proxies with liquidity benchmarks as well as with realized variance estimates. Both benchmarks and volatility measures are obtained from high-frequency data. Our [...] Read more.
This paper examines whether liquidity proxies based on different daily prices and quotes approximate latent liquidity. We compare percent-cost daily liquidity proxies with liquidity benchmarks as well as with realized variance estimates. Both benchmarks and volatility measures are obtained from high-frequency data. Our results show that liquidity proxies based on high-low-open-close prices are more correlated and display higher mutual information with volatility estimates than with liquidity benchmarks. The only percent-cost proxy that indicates higher dependency with liquidity benchmarks than with volatility estimates is the Closing Quoted Spread based on the last bid and ask quotes within a day. We consider different sampling frequencies for calculating realized variance and liquidity benchmarks, and find that our results are robust to it. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Network Analysis of Multivariate Transfer Entropy of Cryptocurrencies in Times of Turbulence
Entropy 2020, 22(7), 760; https://doi.org/10.3390/e22070760 - 11 Jul 2020
Cited by 7 | Viewed by 1474
Abstract
We investigate the effects of the recent financial turbulence of 2020 on the market of cryptocurrencies taking into account the hourly price and volume of transactions from December 2019 to April 2020. The data were subdivided into time frames and analyzed the directed [...] Read more.
We investigate the effects of the recent financial turbulence of 2020 on the market of cryptocurrencies taking into account the hourly price and volume of transactions from December 2019 to April 2020. The data were subdivided into time frames and analyzed the directed network generated by the estimation of the multivariate transfer entropy. The approach followed here is based on a greedy algorithm and multiple hypothesis testing. Then, we explored the clustering coefficient and the degree distributions of nodes for each subperiod. It is found the clustering coefficient increases dramatically in March and coincides with the most severe fall of the recent worldwide stock markets crash. Further, the log-likelihood in all cases bent over a power law distribution, with a higher estimated power during the period of major financial contraction. Our results suggest the financial turbulence induce a higher flow of information on the cryptocurrency market in the sense of a higher clustering coefficient and complexity of the network. Hence, the complex properties of the multivariate transfer entropy network may provide early warning signals of increasing systematic risk in turbulence times of the cryptocurrency markets. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Tsallis Entropy for Cross-Shareholding Network Configurations
Entropy 2020, 22(6), 676; https://doi.org/10.3390/e22060676 - 17 Jun 2020
Cited by 1 | Viewed by 978
Abstract
In this work, we develop the Tsallis entropy approach for examining the cross-shareholding network of companies traded on the Italian stock market. In such a network, the nodes represent the companies, and the links represent the ownership. Within this context, we introduce the [...] Read more.
In this work, we develop the Tsallis entropy approach for examining the cross-shareholding network of companies traded on the Italian stock market. In such a network, the nodes represent the companies, and the links represent the ownership. Within this context, we introduce the out-degree of the nodes—which represents the diversification—and the in-degree of them—capturing the integration. Diversification and integration allow a clear description of the industrial structure that were formed by the considered companies. The stochastic dependence of diversification and integration is modeled through copulas. We argue that copulas are well suited for modelling the joint distribution. The analysis of the stochastic dependence between integration and diversification by means of the Tsallis entropy gives a crucial information on the reaction of the market structure to the external shocks—on the basis of some relevant cases of dependence between the considered variables. In this respect, the considered entropy framework provides insights on the relationship between in-degree and out-degree dependence structure and market polarisation or fairness. Moreover, the interpretation of the results in the light of the Tsallis entropy parameter gives relevant suggestions for policymakers who aim at shaping the industrial context for having high polarisation or fair joint distribution of diversification and integration. Furthermore, a discussion of possible parametrisations of the in-degree and out-degree marginal distribution—by means of power laws or exponential functions— is also carried out. An empirical experiment on a large dataset of Italian companies validates the theoretical framework. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Long-Range Dependence in Financial Markets: A Moving Average Cluster Entropy Approach
Entropy 2020, 22(6), 634; https://doi.org/10.3390/e22060634 - 08 Jun 2020
Cited by 5 | Viewed by 1190
Abstract
A perspective is taken on the intangible complexity of economic and social systems by investigating the dynamical processes producing, storing and transmitting information in financial time series. An extensive analysis based on the moving average cluster entropy approach has evidenced market and horizon [...] Read more.
A perspective is taken on the intangible complexity of economic and social systems by investigating the dynamical processes producing, storing and transmitting information in financial time series. An extensive analysis based on the moving average cluster entropy approach has evidenced market and horizon dependence in highest-frequency data of real world financial assets. The behavior is scrutinized by applying the moving average cluster entropy approach to long-range correlated stochastic processes as the Autoregressive Fractionally Integrated Moving Average (ARFIMA) and Fractional Brownian motion (FBM). An extensive set of series is generated with a broad range of values of the Hurst exponent H and of the autoregressive, differencing and moving average parameters p , d , q . A systematic relation between moving average cluster entropy and long-range correlation parameters H, d is observed. This study shows that the characteristic behaviour exhibited by the horizon dependence of the cluster entropy is related to long-range positive correlation in financial markets. Specifically, long range positively correlated ARFIMA processes with differencing parameter d 0.05 , d 0.15 and d 0.25 are consistent with moving average cluster entropy results obtained in time series of DJIA, S&P500 and NASDAQ. The findings clearly point to a variability of price returns, consistently with a price dynamics involving multiple temporal scales and, thus, short- and long-run volatility components. An important aspect of the proposed approach is the ability to capture detailed horizon dependence over relatively short horizons (one to twelve months) and thus its relevance to define risk analysis indices. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
The Evolution Characteristics of Systemic Risk in China’s Stock Market Based on a Dynamic Complex Network
Entropy 2020, 22(6), 614; https://doi.org/10.3390/e22060614 - 02 Jun 2020
Cited by 2 | Viewed by 1197
Abstract
The stock market is a complex system with unpredictable stock price fluctuations. When the positive feedback in the market amplifies, the systemic risk will increase rapidly. During the last 30 years of development, the mechanism and governance system of China’s stock market have [...] Read more.
The stock market is a complex system with unpredictable stock price fluctuations. When the positive feedback in the market amplifies, the systemic risk will increase rapidly. During the last 30 years of development, the mechanism and governance system of China’s stock market have been constantly improving, but irrational shocks have still appeared suddenly in the last decade, making investment decisions risky. Therefore, based on the daily return of all a-shares in China, this paper constructs a dynamic complex network of individual stocks, and represents the systemic risk of the market using the average weighting degree, as well as the adjusted structural entropy, of the network. In order to eliminate the influence of disturbance factors, empirical mode decomposition (EMD) and grey relational analysis (GRA) are used to decompose and reconstruct the sequences to obtain the evolution trend and periodic fluctuation of systemic risk. The results show that the systemic risk of China’s stock market as a whole shows a downward trend, and the periodic fluctuation of systemic risk has a long-term equilibrium relationship with the abnormal fluctuation of the stock market. Further, each rise of systemic risk corresponds to external factor shocks and internal structural problems. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Systemic Importance of China’s Financial Institutions: A Jump Volatility Spillover Network Review
Entropy 2020, 22(5), 588; https://doi.org/10.3390/e22050588 - 24 May 2020
Cited by 5 | Viewed by 1223
Abstract
The investigation of the systemic importance of financial institutions (SIFIs) has become a hot topic in the field of financial risk management. By making full use of 5-min high-frequency data, and with the help of the method of entropy weight technique for order [...] Read more.
The investigation of the systemic importance of financial institutions (SIFIs) has become a hot topic in the field of financial risk management. By making full use of 5-min high-frequency data, and with the help of the method of entropy weight technique for order preference by similarities to ideal solution (TOPSIS), this paper builds jump volatility spillover network of China’s financial institutions to measure the SIFIs. We find that: (i) state-owned depositories and large insurers display SIFIs according to the score of entropy weight TOPSIS; (ii) total connectedness of financial institution networks reveal that Industrial Bank, Ping An Bank and Pacific Securities play an important role when financial market is under pressure, especially during the subprime crisis, the European sovereign debt crisis and China’s stock market disaster; (iii) an interesting finding shows that some small financial institutions are also SIFIs during the financial crisis and cannot be ignored. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Pricing Constraint and the Complexity of IPO Timing in the Stock Market: A Dynamic Game Analysis
Entropy 2020, 22(5), 546; https://doi.org/10.3390/e22050546 - 13 May 2020
Cited by 1 | Viewed by 960
Abstract
The timing of an initial public offering (IPO) is a complex dynamic game in the stock market. Based on a dynamic game model with the real option, this paper investigates the relationship between pricing constraint and the complexity of IPO timing in the [...] Read more.
The timing of an initial public offering (IPO) is a complex dynamic game in the stock market. Based on a dynamic game model with the real option, this paper investigates the relationship between pricing constraint and the complexity of IPO timing in the stock market, and further discusses its mechanism. The model shows that the IPO pricing constraint reduced the exercise value of the real option of IPO timing, thus restricting the enterprise’s independent timing and promoting an earlier listing. The IPO price limit has a stronger effect on high-trait enterprises, such as technology enterprises. Lowering the upper limit of the pricing constraint increases the probability that enterprises are bound by this restriction during IPO. A high discount cost and stock-market volatility are also reasons for early listing. This paper suggests a theoretical explanation for the mechanism of the pricing constraint on IPO timing in the complex market environment, which is an extension of IPO timing theory, itself an interpretation of the IPO behavior of Chinese enterprises. These findings provide new insights in understanding the complexity of IPOs in relation to the Chinese stock market. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
The Role of Entropy in the Development of Economics
Entropy 2020, 22(4), 452; https://doi.org/10.3390/e22040452 - 16 Apr 2020
Cited by 10 | Viewed by 1501
Abstract
The aim of this paper is to examine the role of thermodynamics, and in particular, entropy, for the development of economics within the last 150 years. The use of entropy has not only led to a significant increase in economic knowledge, but also [...] Read more.
The aim of this paper is to examine the role of thermodynamics, and in particular, entropy, for the development of economics within the last 150 years. The use of entropy has not only led to a significant increase in economic knowledge, but also to the emergence of such scientific disciplines as econophysics, complexity economics and quantum economics. Nowadays, an interesting phenomenon can be observed; namely, that rapid progress in economics is being made outside the mainstream. The first significant achievement was the emergence of entropy economics in the early 1970s, which introduced the second law of thermodynamics to considerations regarding production processes. In this way, not only was ecological economics born but also an entropy-based econometric approach developed. This paper shows that non-extensive cross-entropy econometrics is a valuable complement to traditional econometrics as it explains phenomena based on power-law probability distribution and enables econometric model estimation for non-ergodic ill-behaved (troublesome) inverse problems. Furthermore, the entropy economics has accelerated the emergence of modern econophysics and complexity economics. These new directions of research have led to many interesting discoveries that usually contradict the claims of conventional economics. Econophysics has questioned the efficient market hypothesis, while complexity economics has shown that markets and economies function best near the edge of chaos. Quantum economics has already appeared on the horizon, which recognizes money as a fundamental measurement device in the economy. The development of these sciences may indicate the need to reformulate all mainstream economics from its foundations. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
Article
The Threshold Effect of Leveraged Trading on the Stock Price Crash Risk: Evidence from China
Entropy 2020, 22(3), 268; https://doi.org/10.3390/e22030268 - 26 Feb 2020
Cited by 2 | Viewed by 1129
Abstract
The stock price crash constitutes one part of the complexity in the stock market. We aim to verify the threshold effect of leveraged trading on the stock price crash risk from the perspective of feedback trading. We empirically demonstrate that leveraged trading has [...] Read more.
The stock price crash constitutes one part of the complexity in the stock market. We aim to verify the threshold effect of leveraged trading on the stock price crash risk from the perspective of feedback trading. We empirically demonstrate that leveraged trading has a threshold effect on the stock price crash risk on the basis of monthly data on leveraged trading in the Chinese stock market from January 2014 to December 2016. At a low leverage ratio, leveraged trading reduces the stock price crash risk; however, as the leverage ratio increases and exceeds a certain threshold, leveraged trading asymmetrically increases the stock price crash risk. These findings provide new insights in understanding the complexity in the Chinese stock market. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Allometric Scaling of Mutual Information in Complex Networks: A Conceptual Framework and Empirical Approach
Entropy 2020, 22(2), 206; https://doi.org/10.3390/e22020206 - 12 Feb 2020
Cited by 2 | Viewed by 1178
Abstract
Complexity and information theory are two very valuable but distinct fields of research, yet sharing the same roots. Here, we develop a complexity framework inspired by the allometric scaling laws of living biological systems in order to evaluate the structural features of networks. [...] Read more.
Complexity and information theory are two very valuable but distinct fields of research, yet sharing the same roots. Here, we develop a complexity framework inspired by the allometric scaling laws of living biological systems in order to evaluate the structural features of networks. This is done by aligning the fundamental building blocks of information theory (entropy and mutual information) with the core concepts in network science such as the preferential attachment and degree correlations. In doing so, we are able to articulate the meaning and significance of mutual information as a comparative analysis tool for network activity. When adapting and applying the framework to the specific context of the business ecosystem of Japanese firms, we are able to highlight the key structural differences and efficiency levels of the economic activities within each prefecture in Japan. Moreover, we propose a method to quantify the distance of an economic system to its efficient free market configuration by distinguishing and quantifying two particular types of mutual information, total and structural. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Information Transfer between Stock Market Sectors: A Comparison between the USA and China
Entropy 2020, 22(2), 194; https://doi.org/10.3390/e22020194 - 07 Feb 2020
Cited by 9 | Viewed by 1474
Abstract
Information diffusion within financial markets plays a crucial role in the process of price formation and the propagation of sentiment and risk. We perform a comparative analysis of information transfer between industry sectors of the Chinese and the USA stock markets, using daily [...] Read more.
Information diffusion within financial markets plays a crucial role in the process of price formation and the propagation of sentiment and risk. We perform a comparative analysis of information transfer between industry sectors of the Chinese and the USA stock markets, using daily sector indices for the period from 2000 to 2017. The information flow from one sector to another is measured by the transfer entropy of the daily returns of the two sector indices. We find that the most active sector in information exchange (i.e., the largest total information inflow and outflow) is the non-bank financial sector in the Chinese market and the technology sector in the USA market. This is consistent with the role of the non-bank sector in corporate financing in China and the impact of technological innovation in the USA. In each market, the most active sector is also the largest information sink that has the largest information inflow (i.e., inflow minus outflow). In contrast, we identify that the main information source is the bank sector in the Chinese market and the energy sector in the USA market. In the case of China, this is due to the importance of net bank lending as a signal of corporate activity and the role of energy pricing in affecting corporate profitability. There are sectors such as the real estate sector that could be an information sink in one market but an information source in the other, showing the complex behavior of different markets. Overall, these findings show that stock markets are more synchronized, or ordered, during periods of turmoil than during periods of stability. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Macroprudential Policy in a Heterogeneous Environment—An Application of Agent-Based Approach in Systemic Risk Modelling
Entropy 2020, 22(2), 129; https://doi.org/10.3390/e22020129 - 21 Jan 2020
Cited by 1 | Viewed by 1173
Abstract
Assessment of welfare effects of macroprudential policy seems the most important application of the Dynamic Stochastic General Equilibrium (DSGE) framework of macro-modelling. In particular, the DSGE-3D model, with three layers of default (3D), was developed and used by the European Systemic Risk Board [...] Read more.
Assessment of welfare effects of macroprudential policy seems the most important application of the Dynamic Stochastic General Equilibrium (DSGE) framework of macro-modelling. In particular, the DSGE-3D model, with three layers of default (3D), was developed and used by the European Systemic Risk Board and European Central Bank as a reference tool to formally model the financial cycle as well as to analyze effects of macroprudential policies. Despite the extreme importance of incorporating financial constraints in Real Business Cycle (RBC) models, the resulting DSGE-3D construct still embraces the representative agent idea, making serious analyses of diversity of economic entities impossible. In this paper, we present an alternative to DSGE modelling that seriously departs from the assumption of the representativeness of agents. Within an Agent Based Modelling (ABM) framework, we build an environment suitable for performing counterfactual simulations of the impact of macroprudential policy on the economy, financial system and society. We contribute to the existing literature by presenting an ABM model with broad insight into heterogeneity of agents. We show the stabilizing effects of macroprudential policies in the case of economic or financial distress. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Article
Unexpected Information Demand and Volatility Clustering of Chinese Stock Returns: Evidence from Baidu Index
Entropy 2020, 22(1), 44; https://doi.org/10.3390/e22010044 - 28 Dec 2019
Cited by 3 | Viewed by 1107
Abstract
This paper employs the Baidu Index as the novel proxy for unexpected information demand and shows that this novel proxy can explain the volatility clustering of Chinese stock returns. Generally speaking, these findings suggest that investors in China could take advantage of the [...] Read more.
This paper employs the Baidu Index as the novel proxy for unexpected information demand and shows that this novel proxy can explain the volatility clustering of Chinese stock returns. Generally speaking, these findings suggest that investors in China could take advantage of the Baidu Index to obtain information and then improve their investment decision. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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Concept Paper
What Motivates Speculators to Speculate?
Entropy 2020, 22(1), 59; https://doi.org/10.3390/e22010059 - 31 Dec 2019
Cited by 2 | Viewed by 1398
Abstract
Land speculation that occurs on the urban border can be very problematic to the healthy development of cities—critical to economic growth. Speculative land investors, concerned with profits from trading in landed property, can especially affect developing countries where regulation is often poorly controlled [...] Read more.
Land speculation that occurs on the urban border can be very problematic to the healthy development of cities—critical to economic growth. Speculative land investors, concerned with profits from trading in landed property, can especially affect developing countries where regulation is often poorly controlled and overly bureaucratic. An investigation into the factors motivating land speculators operating in the urban fringe of the city of Shashemene, Ethiopia is examined. The paper, in addition to contributing to the literature, is the second-known attempt and extension of the authors’ pilot research to study the behavior of land speculators in the urban fringe of a growing Ethiopian city. A theoretical framework and conceptual breakdown are put together with historical reference to early land speculation examples. Two questionnaires were separately administered with a representative random sample of 159 members from the local land developer association (i.e., investors) and 24 senior officials from the study area. A principal component analysis categorized the most significant dynamics in controlling land speculation procurements. Results indicated motivational reasoning as the prime cause for speculative activities. Evidence indicated that land speculation is a critical dynamic for self-worth especially with business-oriented persons. Entropy, the disorder of the communicative data, suggests a possible rethinking of the way government should intervene in the urban property market. As such, developmental smart cities in Ethiopia must thoroughly consider the dynamisms of speculative activities and its effects on local housing as it moves forward–in the 2020s. Full article
(This article belongs to the Special Issue Complexity in Economic and Social Systems)
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