Summary:
This paper uses data from China's stock market, money market, real estate market, and credit market to measure the volatility and interactions of the horizontal correlation between China's financial cycles and financial sub-markets from a temporal and spatial perspective. First, we combine the two dimensions of time and space upon which macroprudential policy is based, analyze the operation of China's financial sub-markets in a comprehensive financial cycle and observe horizontal correlations therein. Second, when selecting indicators, in addition to the credit and real estate markets, which are widely used in financial cycle-related research, financial sub-markets with significant horizontal spillover effects, such as the money market and stock market, are used to jointly measure the financial cycle and comprehensively reflect its volatility. Third, based on the generalized variance decomposition spectrum representation analysis framework proposed by Baruník and Křehlík (2018), this paper measures the short-term and long-term horizontal correlations between China's financial sub-markets. The results of this empirical analysis demonstrate that the financial cycle is consistent with horizontally correlated cyclical trends. The accumulation and outbreak of systemic risk in the temporal dimension is closely related to increases in the horizontal correlation in the spatial dimension; the release of systemic risk in the temporal dimension corresponds to a gradual decline in the correlation between financial sub-markets in the spatial dimension. Changes in the horizontal correlation between financial sub-markets are the microfoundation for the simultaneous expansion and decline of financial markets in the temporal dimension. The length of China's financial cycle is approximately 10.33 years and the length of the horizontal correlation cycle in the spatial dimension is about 10.58 years.The cyclical fluctuations in the horizontal correlations in China's financial markets are driven mainly by medium-term and long-term spillovers, and the duration of the spillover linkages is longer than 2 months. After China's real estate cycle peaks, the real estate market shows significant spillovers to the stock and credit markets, which increase the correlation between the stock market, the credit market, and the real estate market and, in turn, transmit volatility to the stock and credit markets. After China's stock market accepts spillovers from the real estate market, the stock market cycle gradually peaks and then continues to make significant spillovers to the real estate and credit markets. After China's credit market receives spillovers from the stock and real estate markets, the credit cycle gradually peaks. Based on the empirical results, this paper proposes the following policy implications from the perspective of macroprudential supervision. First, major financial sub-markets should be included in macroprudential management. The monitoring and evaluation of systemic financial risks should be strengthened in accordance with the laws of temporal and spatial transmission of financial cycles and horizontal correlations. When the financial sub-market cycle peaks, attention should be paid to the enhancement of the spillover effect from this sub-market on other markets. For financial sub-markets that are susceptible to other sub-markets, risk prevention and control measures should be taken before the financial cycle peaks to prevent them from accepting spillovers from other markets and triggering risk resonance. Second, the duration of the policy impact could be better predicted based on the duration of the spillover relationships. When implementing macroprudential policy, the duration of the spillover relationship should be considered to better estimate the policy time lag and issue macroprudential policy guidelines in a timely manner. Monetary policy, credit policy, real estate financial prudential policy, and capital market regulatory policy coordination should be designed to reduce fluctuations in the financial system and negative externalities to the real economy.
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