Financial price dynamics and pedestrian counterflows: a comparison of statistical stylized facts

Herding behavior during the Covid-19 pandemic: a comparison between Asian and European stock markets based on intraday multifractality

With the spread of Covid-19, investors’ expectations changed during 2020, as well as financial markets’ policy responses and the structure of global financial intermediation itself. These dynamics are studied in this paper, which analyzes quarterly changes in herding behavior by quantifying the self-similarity intensity of six stock markets in Asia and Europe. A multifractal detrended fluctuation analysis (MFDFA) is applied, using intraday trade prices with a 15-min frequency from Jan-2020 to Dec-2020. The empirical results confirm that Covid-19 had a significant impact on the efficiency of the stock markets under study, although with a quarterly varying impact. During the first quarter of the year, European stock markets remained efficient compared to Asian markets; in the subsequent two quarters, the Chinese stock market showed significant improvement in its efficiency and became the least inefficient market, with a decline in the market efficiency of the UK and Japan. Furthermore, European markets are more sensitive to asset losses than Asian markets, so investors are more likely to show herding in the former. Herding was at its peak during the 2nd quarter of 2020. These findings could be related to possible market inefficiencies and herding behavior, implying the possibility of investors forming profitable trading strategies.

Pedestrian dynamics at the running of the bulls evidence an inaccessible region in the fundamental diagram

We characterize the dynamics of runners in the famous "Running of the Bulls" Festival by computing the individual and global velocities and densities, as well as the crowd pressure. In contrast with all previously studied pedestrian systems, we unveil a unique regime in which speed increases with density that can be understood in terms of a time-dependent desired velocity of the runners. Also, we discover the existence of an inaccessible region in the speed-density state diagram that is explained by falls of runners. With all these ingredients, we propose a generalization of the pedestrian fundamental diagram for a scenario in which people with different desired speeds coexist.

Properties of balanced flows with bottlenecks: Common stylized facts in finance and vibration-driven vehicles

We study experimentally the properties of the flow of mechanical vibration-driven vehicles confined in two chambers connected through a narrow opening. We report that the density of particles around the opening presents critical behavior and scaling properties. By mapping this density to the financial market price, we document that the main stylized facts observed in financial systems have their counterparts in the mechanical system. The experimental model accurately reproduces financial properties such as scaling of the price fluctuation, volatility clustering, and multiscaling.

An Econophysics Study of the S&P Global Clean Energy Index

The study of how financial markets behave continues to be interesting. The existence of more and more data and the development of statistical techniques are some reasons for the increase in research in finance. However, the difficulty in understanding some markets’ behavior is a continuous challenge. In this context, a new research area called Econophysics has emerged, which is constantly increasing in size. We propose in this work to use methodologies related to Econophysics to analyze one stock index composed of firms producing clean energy (S&P Global Clean Energy Index) and compare it with the New York Stock Exchange (NYSE) as a stock market benchmark and with the price of crude oil. In a context where environmental issues are on the agenda, this is an important area of research, because it could help investors to make their decisions. Our results show that the clean energy index seems to have higher time serial dependence than the others, and is less exposed to oil price than the NYSE.

Avalanche effects near nanojunctions

In this article, we perform a computational investigation of a nanopore connected to external fluidic reservoirs of asymmetric geometries. The asymmetry between the reservoirs is achieved by changing the cross-sectional areas, and the reservoirs are designated as the micropore reservoir and macropore reservoir. When an electric field is applied, which is directed from the macropore towards the micropore reservoir, we observe local nonequilibrium chaotic current oscillations. The current oscillations originate at the micropore-nanopore interface owing to the local cascade of ions; we refer to this phenomenon as the "avalanche effects." We mathematically quantify chaos in terms of the maximum Lyapunov exponent. The maximum Lyapunov exponent exhibits a monotonic increase with the applied voltage and the macropore reservoir diameter. The temporal power spectra maps of the chaotic currents depict a low-frequency "1/f"-type dynamics for the voltage chaos and "1/f^{2}"-type dynamics for the macropore reservoir chaos. The results presented here offer avenues to manipulate ionic diodes and fluidic pumps.

Physics and financial economics (1776-2014): puzzles, Ising and agent-based models

This short review presents a selected history of the mutual fertilization between physics and economics--from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistical physics. Recent extensions in terms of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it did not cover the dynamical field of agent-based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the 'Emerging Intelligence Market Hypothesis' to reconcile the pervasive presence of 'noise traders' with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets.

Reducing financial avalanches by random investments

Building on similarities between earthquakes and extreme financial events, we use a self-organized criticality-generating model to study herding and avalanche dynamics in financial markets. We consider a community of interacting investors, distributed in a small-world network, who bet on the bullish (increasing) or bearish (decreasing) behavior of the market which has been specified according to the S&P 500 historical time series. Remarkably, we find that the size of herding-related avalanches in the community can be strongly reduced by the presence of a relatively small percentage of traders, randomly distributed inside the network, who adopt a random investment strategy. Our findings suggest a promising strategy to limit the size of financial bubbles and crashes. We also obtain that the resulting wealth distribution of all traders corresponds to the well-known Pareto power law, while that of random traders is exponential. In other words, for technical traders, the risk of losses is much greater than the probability of gains compared to those of random traders.