Industry Portfolio Volatility Connections and Industry Portfolio Returns
Year: 2026
Type: article
Abstract: ABSTRACT This paper tracks dynamic connections that form among daily US industry portfolio return volatilities using a Bayesian time‐varying parameter VAR model. Market participants often focus on sectors to filter vast amounts of information, and this focus results in cross‐industry return predictability. We characterise connections that form over the short‐, medium‐ and long‐term, analysing their role as indicators of sectoral uncertainties. These volatility‐based connections create a network structure that reflects co‐movement across different industries. By capturing these network dynamics, we assess their usefulness in predicting US industry portfolio returns. Our results show that network connections contain economically meaningful information for future industry portfolio returns, offering significant gains in both point and density forecasts.
DOI: 10.1002/ijfe.70208
Institutions: University of Liverpool, Durham University
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,400
OpenAlex ID: W7155650484