Unveiling multiscale spatiotemporal dynamics of volatility in high-frequency financial markets.

This study explores the intricate dynamics of volatility within high-frequency financial markets, focusing on 225 of Chinese listed companies from 2016 to 2023. Utilizing 5-minute high-frequency data, we analyze the realized volatility of individual stocks across six distinct time scales: 5-minute, 10-minute, 30-minute, 1-hour, 2-hour, and 4-hour intervals. Our investigation reveals a consistent power law decay in the auto-correlation function of realized volatility across all time scales.

Exploring Market State and Stock Interactions on the Minute Timescale.

A stock market is a non-stationary complex system. The stock interactions are important for understanding the state of the market. However, our knowledge on the stock interactions on the minute timescale is limited.

Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.

The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.