Proximity to Explosive Synchronization Determines Network Collapse and Recovery Trajectories in Neural and Economic Crises.

When complex systems move away from criticality-a balance between order and chaos-they are no longer optimized. Furthermore, when criticality is lost too quickly, or recovery is delayed, system damage can result. However, the mechanism for these abnormally fast or slow critical transitions remains unknown.

The contagion effect of heterogeneous investor groups.

This paper suggests an alternative approach to measuring systemic risk in financial markets by examining the interconnectedness among heterogeneous investors. Utilizing variance decomposition and a trading database from the Korea Stock Exchange spanning 2002-2018, we find that systemic risk, as quantified by total connectedness based on microlevel investor activity, intensifies during both domestic and global financial crises. In addition, our analysis indicates that retail investors, often termed noise traders, are pivotal contributors to the propagation of financial shocks.

Multifractal analysis of social media use in financial markets.

We analyze the nonlinear properties of social media activity(SMA) using the multifractal detrended fluctuation analysis (MF-DFA) method. Social media data related to the stock market are gathered from social media platforms. Using data on over 2000 firms in the Korean stock market for 2018-2020, we study social media activity and its differences to evaluate associated nonlinear and statistical properties.

The dynamics of the aggressive order during a crisis.

We investigate the dynamics of aggressive order in the financial market to further understand volatility. To analyze aggressive order, market orders in the order book are scrutinized. The market orders have different degrees of aggressiveness; therefore, we categorize market orders into four types: types Zero, One, A, and B, of which type B is the most aggressive.

Understanding Financial Market States Using an Artificial Double Auction Market.

The ultimate value of theories describing the fundamental mechanisms behind asset prices in financial systems is reflected in the capacity of such theories to understand these systems. Although the models that explain the various states of financial markets offer substantial evidence from the fields of finance, mathematics, and even physics, previous theories that attempt to address the complexities of financial markets in full have been inadequate. We propose an artificial double auction market as an agent-based model to study the origin of complex states in financial markets by characterizing important parameters with an investment strategy that can cover the dynamics of the financial market.

Brain networks maintain a scale-free organization across consciousness, anesthesia, and recovery: evidence for adaptive reconfiguration.

Background: Loss of consciousness is an essential feature of general anesthesia. Although alterations of neural networks during anesthesia have been identified in the spatial domain, there has been relatively little study of temporal organization.

Methods: Ten healthy male volunteers were anesthetized with an induction dose of propofol on two separate occasions.

Understanding volatility correlation behavior with a magnitude cross-correlation function.

We propose an approach for analyzing the basic relation between correlation properties of the original signal and its magnitude fluctuations by decomposing the original signal into its positive and negative fluctuation components. We use this relation to understand the following phenomenon found in many naturally occurring time series: the magnitude of the signal exhibits long-range correlation, whereas the original signal is short-range correlated. The applications of our approach to heart rate variability signals and high-frequency foreign exchange rates reveal that the difference between the correlation properties of the original signal and its magnitude fluctuations is induced by the time organization structure of the correlation function between the magnitude fluctuations of positive and negative components.