区制转换视角下资产风险非对称性溢出研究

A Study on the Asymmetric Spillover of Asset Risk from the Perspective of Regional Transformation

摘要: 随着全球市场进一步发展，全球金融市场中的资产之间的波动溢出效应正变得越来越复杂，越来越密切。金融资产如具有代表性的股票、加密货币、大宗商品、外汇等资产价格风险溢出，在全球不同市场间显著呈现出典型的非对称性。此外，在不同的经济情况下，尤其是在高低金融压力之下，资产间价格波动的风险会随着金融大环境的变化而变化，具有一定的区制转换特征。鉴于此，本文参考使用具有非线性特征的平滑转换向量自回归模型(smooth-transition vector autoregression, STVAR)，以中国、美国等15个国家的股票、加密货币、大宗商品、外汇等共计28种资产为研究对象，系统探究区制转换背景下多资产的风险非对称性传染机制。具体来说，使用经济政策不确定性(EPU)和全球金融压力指数(FCI)作为转换变量来衡量金融状况，并且在此基础上构建了多维度资产风险传染的非对称矩阵，分析在单区制不同金融状况下，即高低政策不确定性、高低金融压力下不同的金融资产风险溢出状况。研究发现，在高金融压力下，金融市场的波动性较大，资产的风险传染效应更为显著。经济政策不确定性与金融压力的叠加，加剧了市场风险偏好收敛与资金向安全资产集聚，进一步放大了核心资产的波动输出能力与跨市场传导效率。黄金通过资金配置与情绪传导实现跨市场溢出，能源大宗商品依托供需波动与成本传导影响全球经济，加密货币则因市场定位与投资者结构差异呈现溢出异质性。

Abstract: As global markets continue to evolve, the volatility spillover effects among assets within international financial markets are becoming increasingly complex and interconnected. Price risks for financial assets—including representative equities, cryptocurrencies, commodities, and foreign exchange—exhibit pronounced asymmetric spillovers across different global markets. Furthermore, under varying economic conditions, particularly during periods of high or low financial stress, the volatility risks associated with asset price fluctuations shift in response to broader financial environment changes, demonstrating distinct regional conversion characteristics. Given this context, this paper employs the smooth-transition vector autoregression (STVAR) model, which incorporates nonlinear characteristics. Using 28 assets—including stocks, cryptocurrencies, commodities, and foreign exchange—from 15 countries and regions (such as China and the United States), it systematically investigates the asymmetric risk contagion mechanisms across multiple assets under regional transition scenarios. Specifically, the Economic Policy Uncertainty (EPU) and the Financial Conditions Index (FCI) are employed as transition variables to gauge financial conditions. Based on this, a multidimensional asymmetric risk contagion matrix for assets is constructed to analyze risk spillover patterns across financial assets under different financial conditions within a single regime—namely, high versus low policy uncertainty and high versus low financial stress. The findings reveal that under high financial stress, market volatility increases significantly, amplifying the risk contagion effects across assets. The combination of economic policy uncertainty and financial pressure intensifies market risk aversion and capital flight toward safe assets, further amplifying the volatility output capacity of core assets and cross-market transmission efficiency. Gold achieves cross-market spillover through capital allocation and sentiment transmission; energy commodities influence the global economy via supply-demand fluctuations and cost pass-through; while cryptocurrencies exhibit heterogeneous spillover due to differences in market positioning and investor structures.