We use variance decompositions from high-dimensional vector autoregressions to characterize connectedness in 19 key commodity return volatilities, 2011-2016. We study both static (full-sample) and dynamic (rolling-sample) connectedness. We summarize and visualize the results using tools from...

Using a recently-developed measure of financial market spillovers, we provide an empirical analysis of return and volatility spillovers among five equity markets in the Americas: Argentina, Brazil, Chile, Mexico and the U.S. The results indicate that both return and volatility spillovers vary...

Using a generalized vector autoregressive framework in which forecast-error variance decompositions are invariant to variable ordering, we propose measures of both total and directional volatility spillovers. We use our methods to characterize daily volatility spillovers across U.S. stock, bond,...

We provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, we formulate and examine precise and separate measures of return spillovers and volatility spillovers. Our framework facilitates study of both non-crisis and crisis episodes,...

The authors provide a simple and intuitive measure of interdependence of asset returns and/or volatilities. In particular, they formulate and examine precise and separate measures of return spillovers and volatility spillovers. The authors framework facilitates study of both noncrisis and crisis...

Notwithstanding its impressive contributions to empirical financial economics, there remains a significant gap in the volatility literature, namely its relative neglect of the connection between macroeconomic fundamentals and asset return volatility. We progress by analyzing a broad...