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The story of econophysics
\"This title will appeal to the lay-reader with an interest in the history of what is today termed 'Econophysics', looking at various works throughout the ages that have led to the emergence of this field. It begins with a discussion of the philosophers and scientists who have contributed to this discipline, before moving on to considering the contributions of different institutions, books, journals and conferences in nurturing the subject\"-- Provided by publisher.
Book
Permutation Entropy and Its Main Biomedical and Econophysics Applications: A Review
Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculating entropy based on permutation patterns (that is, permutations defined by the order relations among values of a time series) has received a lot of attention in the last years, especially for the understanding of complex and chaotic systems. Permutation entropy directly accounts for the temporal information contained in the time series; furthermore, it has the quality of simplicity, robustness and very low computational cost. To celebrate the tenth anniversary of the original work, here we analyze the theoretical foundations of the permutation entropy, as well as the main recent applications to the analysis of economical markets and to the understanding of biomedical systems.
Journal Article
Probabilistic sharing solves the problem of costly punishment
Cooperators that refuse to participate in sanctioning defectors create the second-order free-rider problem. Such cooperators will not be punished because they contribute to the public good, but they also eschew the costs associated with punishing defectors. Altruistic punishers-those that cooperate and punish-are at a disadvantage, and it is puzzling how such behaviour has evolved. We show that sharing the responsibility to sanction defectors rather than relying on certain individuals to do so permanently can solve the problem of costly punishment. Inspired by the fact that humans have strong but also emotional tendencies for fair play, we consider probabilistic sanctioning as the simplest way of distributing the duty. In well-mixed populations the public goods game is transformed into a coordination game with full cooperation and defection as the two stable equilibria, while in structured populations pattern formation supports additional counterintuitive solutions that are reminiscent of Parrondoʼs paradox.
Journal Article
Review of the gravity model: origins and critical analysis of its theoretical development
This article presents a bibliographic review of the gravitational model in international trade from when it was first associated with Newton's law of universal gravitation. Firstly, I will introduce the concept of gravity in commerce as originally intended by Isard (Q J Econ 68(2):305–320, 1954) in relation to Tinbergen and Tobler’s approaches. Secondly, I will analyse the theoretical roots of international economics according to several authors, including McCallum, Anderson and van Wincoop, Krugman, Tranos, and Nijkamp. Thirdly, attention will be drawn to the evolution of the ideas of the authors mentioned above upon Isard’s initial approach rooted in physics. Furthermore, I will focus on how the tool rooted in physics can be applied or adapted to international trade. Throughout this article, I will try to keep the econophysical nature of this model.
Journal Article
Cross-correlations between volume change and price change
In finance, one usually deals not with prices but with growth rates R, defined as the difference in logarithm between two consecutive prices. Here we consider not the trading volume, but rather the volume growth rate R, the difference in logarithm between two consecutive values of trading volume. To this end, we use several methods to analyze the properties of volume changes |R|, and their relationship to price changes |R|. We analyze 14,981 daily recordings of the Standard and Poor's (S & P) 500 Index over the 59-year period 1950-2009, and find power-law cross-correlations between |R| and |R| by using detrended cross-correlation analysis (DCCA). We introduce a joint stochastic process that models these cross-correlations. Motivated by the relationship between |R| and |R|, we estimate the tail exponent [Formula: see text] of the probability density function P(|R|) ~ |R|⁻¹⁻[Formula: see text] for both the S & P 500 Index as well as the collection of 1819 constituents of the New York Stock Exchange Composite Index on 17 July 2009. As a new method to estimate [Formula: see text], we calculate the time intervals τq between events where R > q. We demonstrate that [Formula: see text]q, the average of τq, obeys [Formula: see text]q ~ q[Formula: see text]. We find [Formula: see text] [almost equal to] 3. Furthermore, by aggregating all τq values of 28 global financial indices, we also observe an approximate inverse cubic law.
Journal Article
Herd behavior in a complex adaptive system
In order to survive, self-serving agents in various kinds of complex adaptive systems (CASs) must compete against others for sharing limited resources with biased or unbiased distribution by conducting strategic behaviors. This competition can globally result in the balance of resource allocation. As a result, most of the agents and species can survive well. However, it is a common belief that the formation of a herd in a CAS will cause excess volatility, which can ruin the balance of resource allocation in the CAS. Here this belief is challenged with the results obtained from a modeled resource-allocation system. Based on this system, we designed and conducted a series of computer-aided human experiments including herd behavior. We also performed agent-based simulations and theoretical analyses, in order to confirm the experimental observations and reveal the underlying mechanism. We report that, as long as the ratio of the two resources for allocation is biased enough, the formation of a typically sized herd can help the system to reach the balanced state. This resource ratio also serves as the critical point for a class of phase transition identified herein, which can be used to discover the role change of herd behavior, from a ruinous one to a helpful one. This work is also of value to some fields, ranging from management and social science, to ecology and evolution, and to physics.
Journal Article
Information Transfer between Stock Market Sectors: A Comparison between the USA and China
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.
Journal Article
Complex Financial Networks
The concepts and dynamic processes related to complex financial networks (CFNs) are explored in this review article. After providing a definition of CFNs, we discuss the most important dynamic process associated with them, i.e., contagion. We then examine the relationship between interconnectedness and systemic risk in CFNs. Next, we discuss approaches to the measurement of systemic risk and the challenges associated with this task. Finally, we highlight three research avenues that, in our opinion, are crucial for a better understanding of the dynamics of the contagion process in CFNs: loss distribution regime, endogenous complex networks, and multilayer complex networks.
Journal Article
Do all shocks produce embedded herding and bubble? An empirical observation of the Indian stock market
Herding has a history of igniting large, irrational market ups and downs, usually based on a lack of fundamental support. Intuitively, most herds start with an external shock. This empirical study seeks to detect shock-induced herding and the creation of nascent bubbles in the Indian stock market. Initially, the multifractal form of the detrended fluctuation analysis was applied. Then the Reformulated Hurst exponent for the Bombay stock exchange (BSE) was determined using Kantelhardt’s calibration. The investigation found evidence of high-level herding and a bubble in 2012, with a high value of Hurst Exponent (0.7349). The other years of the research period (2011, 2013, 2016, 2018, 2020–2021) observed mild to significant herding with comparatively lower Hurst values. The results confirm that herding behavior occurs during a crisis and harsh situations emitting shocks. The study concludes that shock-based herding is prevalent in all six shocks: the economic meltdown, commodities and currency devaluation, geo-political problems, the Central Bank’s decision on liquidity management, and the Pandemic. Additionally, the years following the Financial Crisis and the years of the Pandemic are when herding and bubble are prominent. AcknowledgmentsWe thank Dr. Bikramaditya Ghosh (Associate Professor, Symbiosis International University, Bangalore, India) for motivating us in this research. We also thank Dr. Natchimuthu N (Assistant Professor, Commerce, CHRIST (Deemed to be University), Bangalore, India) and Dr. Mahesh E. (Assistant Professor, Economics, CHRIST (Deemed to be University), Bangalore, India) for their support throughout this study.
Journal Article