Volatility spillover along the supply chains: a network analysis on economic links

Theo Berger and Ramazan Gençay

Abstract

We introduce a financial network approach to quantify the impact of counterparty risk on firms' daily market risk, measured via conditional volatility. Translating conditional volatility into a value-at-risk (VaR) framework allows us to identify extreme losses beyond an estimated loss limit and to determine volatile market regimes. We find that suppliers are exposed to additional fundamental risks that are not captured by their market beta, and these get transferred along supply chains. The identified risk spillover affects both the coverage and the quality of suppliers' market risk assessments. If customers experience large losses beyond their individual VaR limit, suppliers' variance forecasts increase by (up to) 1%, and the probability of suppliers' extreme losses doubles the next day.