关键词: 金融市场, 相依结构, 相依关系, 耦合联动效应, 系统性风险

Abstract: The financial system is an important foundation for economic development and an important source of systemic risks in China. As an important window for the interaction between the real economy and financial economy, the real estate market also plays an important role in the formation and spread of risks. For financial risks, it is necessary to coordinate the coupling mechanism between the financial markets and fully understand the spillover mechanism of financial risk inside and outside the financial market.
The overall “coupling co-movement” of the financial market reflects a kind of correlation. WLMC can not only deal with the time-varying co-movement between two markets but also describe the overall time-varying co-movement among multiple markets, capture the co-movement characteristics of multiple time series at different frequencies, and explain how this co-movement evolves over time. This study uses the wavelet local multiple correlation (WLMC) to explore the mutual influence and co-movement between multiple markets, and the Vine-Copula model to verify the co-movement structure between multiple markets. The WLMC model utilizes the maximal overlap discrete wavelet transform (MODWT) to obtain the wavelet coefficients as the time series input for further in-depth analysis. China’s important financial markets are currency, bonds, foreign exchange, and gold markets. Simultaneously, its real estate market is closely connected to the real economy and financial markets. Therefore, this study selects the stock, bond, currency, foreign exchange, gold, and real estate markets as research objects to explore the overall co-movement structure and dynamic time-frequency co-movement among multiple markets. We use the daily income data of stocks, bonds, currencies, foreign exchange, gold, and real estate markets from July 27, 2005 to August 13, 2021 as samples, and the sample data are mainly from the WIND and CSMAR databases. The daily rate of return for each market is obtained by logarithmic processing of the closing price data for each market. After sorting, 3888 valid samples are obtained.
The research finds that: First, financial markets have stable characteristics of high-frequency low positive co-movement and low-frequency high positive co-movement. Second, in addition to the stock market, there is no stable and high-strength coupling co-movement between other financial sub-markets and the real estate market. Third, during the sample period, the financial system and the real estate market are closely coupled, and the stock market is the bridge between the financial market and real estate market. So the financial system and real economy are a positive sum game of symbiosis, mutual prosperity, and mutual promotion. To prevent systemic risks, we need to promote the deep integration of finance and real economy. The co-movement structure of multiple markets and key hub markets is crucial for timely blocking risk propagation paths, preventing and resolving financial risks. Therefore, in the process of risk prevention and control, we must focus on the spillover effect of financial market risks on the real estate market, and the spillover of risks on the real economy. Whereafter, the sliding window method can be adopted to effectively identify the structural changes in market co-movement before and after the crisis through different time windows, and then the changes in systemic risk can be studied. In addition, a mixed frequency model can also be used to study the relationship among economic fundamentals, economic policy uncertainty, investor sentiment factors, and market co-movement characteristics.

Key words: financial market, interdependent structure, interdependent relationship, coupling effect, systemic risk