Industry Portfolio Volatility Connections and Industry Portfolio Returns
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.
Authors
- Michael Ellington (ORCID: https://orcid.org/0000-0003-0264-7572)
- Michalis P. Stamatogiannis (ORCID: https://orcid.org/0000-0002-7283-7550)
- Yawen Zheng (ORCID: https://orcid.org/0000-0002-3269-6837)
Institutions
- University of Liverpool (GB)
- Durham University (GB)
Publication Details
- Journal
- International Journal of Finance & Economics
- Published
- 2026-04-24
- DOI
- https://doi.org/10.1002/ijfe.70208
- Primary Topic
- Financial Risk and Volatility Modeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00