Posts

I adopt a network perspective to provide a microfoundation for aggregate volatility risk. Theoretically, I develop a dynamic multisector model and show that intersectoral idiosyncratic volatility spillovers—arising from a persistent and asymmetric trade network—generate both the origins and variations in aggregate volatility. These spillovers affect asset prices through the volatility-risk channel and, when investors prefer early resolution of uncertainty, through the cash-flow news channel as well. Empirically, I construct two theory-motivated network factors that capture the dynamics of idiosyncratic volatility spillovers and show that they significantly predict future aggregate volatility and are priced as volatility risk factors.