Fat Tails, Serial Dependence, and Implied Volatility Index Connections

This paper accounts for fat tails and serial dependence for implied volatility index network connections among equity and commodity markets using Bayesian vector heterogeneous autoregressions. I analyse the information content of such connections over short-, medium- and long-horizons for predicting underlying asset returns and whether conventional asset pricing risk factors explain the variation of portfolios that sort on directional connections. Results highlight the importance of accounting for network connections within the information set when forecasting underlying asset returns, and that investors can trade on directional connections at horizons of less than month to hedge against temporary adverse changes to investment opportunities