ABSTRACT
Most of the existing literature use volatility to measure risk and concentrate on modeling volatility spillover. Volatility is an important instrument in finance and macroeconomics. However, it can only adequately represent small risks. When monitoring financial risk, the probability of a large adverse market movement is always of greater practical concern. Volatility alone cannot satisfactorily capture risk in scenarios of occasionally occurring extreme market movement. Moreover, it includes both gains and losses in a symmetric way. This chapter discusses the concept of Granger causality in risk. A Granger-type regression-based test is equivalent to the uniform-weighting-based test. As is well known, Granger causality is not a relationship between 'causes' and 'effects'. Instead, it is defined in terms of incremental predictive ability. This concept is suitable for the purpose of predicting and monitoring risk spillover and provides valuable information for investment decisions, supervisor decisions, risk capital allocation and external regulation.
