Xie He

This study examines whether endogenous inter-firm volatility spillovers amplify industry risk in China's new energy sector. It constructs a leave-one-out industry index under a market-industry two-factor framework, extracts residual stock returns, and estimates firm-level residual conditional volatility. Based on these volatility series, the LASSO-VAR connectedness approach is employed to identify the direction, magnitude, and structure of firm-specific volatility spillovers across firms. The findings suggest that industry risk is driven not only by external shocks, but also by amplification mechanisms operating within the inter-firm network that are not captured by common factor models alone.

This study investigates the risk spillovers of economic policy uncertainty across macroeconomic and financial systems in China and the United States using mixed-frequency data. Employing a mixed-frequency connectedness approach, the analysis integrates monthly macroeconomic indicators with weekly financial variables to more accurately capture cross-country transmission mechanisms.

We investigate the role of common global factors in driving exchange rate behavior, with a particular focus on volatility and volatility co-movement. Utilizing the multivariate factor stochastic volatility model, we identify that exchange rate volatilities are best explained by a three-factor model. The results highlight the role of global factors in shaping currency dynamics.

This study proposes a framework that decomposes volatility and higher-moment kurtosis into good and bad volatility/kurtosis related to positive and negative shocks. It analyzes spillover effects between sustainable and traditional investments and shows that bad volatility spillovers dominate good volatility spillovers during most periods, while good kurtosis spillovers usually dominate bad kurtosis spillovers.