Complexity in Economic and Social Systems
Drożdż, Stanisław (editor)
Kwapień, Jarosław (editor)
Oświęcimka, Paweł (editor)
There is no term that better describes the essential features of human society than complexity. On various levels, from the decision-making processes of individuals, through to the interactions between individuals leading to the spontaneous formation of groups and social hierarchies, up to the collective, herding processes that reshape whole societies, all these features share the property of irreducibility, i.e., they require a holistic, multi-level approach formed by researchers from different disciplines. This Special Issue aims to collect research studies that, by exploiting the latest advances in physics, economics, complex networks, and data science, make a step towards understanding these economic and social systems. The majority of submissions are devoted to financial market analysis and modeling, including the stock and cryptocurrency markets in the COVID-19 pandemic, systemic risk quantification and control, wealth condensation, the innovation-related performance of companies, and more. Looking more at societies, there are papers that deal with regional development, land speculation, and the-fake news-fighting strategies, the issues which are of central interest in contemporary society. On top of this, one of the contributions proposes a new, improved complexity measure.
Keywordsvolatility clustering; Baidu Index; information demand; generalized autoregressive conditional heteroscedasticity model (GARCH); mixture of distribution hypothesis; speculation; land acquisition; motivation; real estate; development; Ethiopia; systemic risk; macroprudential policy; agent-based modelling; inequality; central-banking; information transfer; transfer entropy; stock markets; econophysics; complexity science; information theory; economic complexity; evolutionary dynamics; network theory; leveraged trading; stock price crash risk; threshold effect; complexity in stock market; entropy economics; non-extensive cross-entropy econometrics; non-ergodic ill-behaved inverse problems; general system theory; non-linear dynamics; complex adaptive systems; homo oeconomicus; edge of chaos; complexity economics; pricing constraint; IPO timing; dynamic game model; real option; complexity of IPOs; financial institution; complex network; jump volatility; entropy weight TOPSIS; structural entropy; stock market; EMD; cluster-entropy; Shannon-entropy; financial markets; time series; dynamics; Tsallis entropy; copula functions; cross-shareholding network; finance; cryptocurrencies; multivariate transfer entropy; complex networks; liquidity proxy; liquidity benchmark; volatility estimate; correlation coefficient; partial determination; mutual information; forecasting market risk; value at risk; extreme returns; peaks over threshold; self-exciting point process; discrete-time models; generalized Pareto distribution; dynamical complexity; universal complexity measure; irreversible processes; entropies; entropic susceptibilities; complex systems; multifractal analysis; detrended cross-correlations; minimal spanning tree; wealth condensation; agent-based computational economics; bargaining; gain function; macroeconomics; innovative activity; manufacturing industry; conjunctural movements; cybernetics; feedback loops; correspondence analysis; Polish Green Island effect; Red Queen effect; Kondratieff waves; power law; Zipf law; gender productivity gap; fake news; rumor spreading; Nash equilibrium; evolutionarily stable strategies; evolutionary information search dynamics; nonlinear dynamics; chaos; time series analysis; stock exchange market; Lyapunov; recurrence plots; BDS; correlation dimension; GARCH model; measure of economic development; websites; public administration sector; municipality; four-colour theorem; prosumption; platforms for participation; location quotient; dual graph; Euler characteristic; n/a
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Publication date and placeBasel, Switzerland, 2021
Information technology industries