This paper proposes a new method for measuring both total and directional volatility spillovers across financial markets. The authors use a generalized vector autoregressive (VAR) framework that allows for forecast-error variance decompositions invariant to variable ordering. This approach enables the measurement of directional volatility spillovers, which is crucial for understanding the flow of volatility between markets. The authors apply their methods to analyze daily volatility spillovers across U.S. stock, bond, foreign exchange, and commodities markets from January 1999 through January 2010. The study finds that cross-market volatility spillovers were limited until the global financial crisis began in 2007. As the crisis intensified, volatility spillovers increased significantly, with particularly important spillovers from the stock market to other markets following the collapse of Lehman Brothers in September 2008. The authors also identify several key periods of volatility spillovers, including the tech bubble burst in 2000, the Iraqi crisis in 2002, and the global financial crisis from 2007 to 2009. The authors develop a total volatility spillover index and directional spillover measures, which are used to assess the extent and direction of volatility transmission between markets. They find that net volatility spillovers from the stock market were significant during the global financial crisis, with the stock market transmitting volatility to other markets. Similarly, the bond market was a source of volatility spillovers during certain periods, and the commodity market was a net transmitter of volatility during 2002-2003 and in the second half of 2009. The study also highlights the importance of directional spillovers in understanding the dynamics of financial markets. The authors show that volatility spillovers can vary significantly over time and that the global financial crisis was a major period of increased volatility spillovers. The results suggest that financial markets are interconnected, and that volatility can spread rapidly across markets during times of crisis. The authors conclude that their method provides a useful tool for monitoring and understanding volatility spillovers in financial markets.This paper proposes a new method for measuring both total and directional volatility spillovers across financial markets. The authors use a generalized vector autoregressive (VAR) framework that allows for forecast-error variance decompositions invariant to variable ordering. This approach enables the measurement of directional volatility spillovers, which is crucial for understanding the flow of volatility between markets. The authors apply their methods to analyze daily volatility spillovers across U.S. stock, bond, foreign exchange, and commodities markets from January 1999 through January 2010. The study finds that cross-market volatility spillovers were limited until the global financial crisis began in 2007. As the crisis intensified, volatility spillovers increased significantly, with particularly important spillovers from the stock market to other markets following the collapse of Lehman Brothers in September 2008. The authors also identify several key periods of volatility spillovers, including the tech bubble burst in 2000, the Iraqi crisis in 2002, and the global financial crisis from 2007 to 2009. The authors develop a total volatility spillover index and directional spillover measures, which are used to assess the extent and direction of volatility transmission between markets. They find that net volatility spillovers from the stock market were significant during the global financial crisis, with the stock market transmitting volatility to other markets. Similarly, the bond market was a source of volatility spillovers during certain periods, and the commodity market was a net transmitter of volatility during 2002-2003 and in the second half of 2009. The study also highlights the importance of directional spillovers in understanding the dynamics of financial markets. The authors show that volatility spillovers can vary significantly over time and that the global financial crisis was a major period of increased volatility spillovers. The results suggest that financial markets are interconnected, and that volatility can spread rapidly across markets during times of crisis. The authors conclude that their method provides a useful tool for monitoring and understanding volatility spillovers in financial markets.