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.

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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
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article

Industry Portfolio Volatility Connections and Industry Portfolio Returns

Michael Ellington, Michalis P. Stamatogiannis, Yawen Zheng
International Journal of Finance & Economics
Financial Risk and Volatility Modeling
article

Industry Portfolio Volatility Connections and Industry Portfolio Returns

Michael Ellington, Michalis P. Stamatogiannis, Yawen Zheng
article en

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.

International Journal of Finance & Economics
University of Liverpool (GB), Durham University (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Financial Risk and Volatility Modeling
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Industry Portfolio Volatility Connections and Industry Portfolio Returns — Michael Ellington, Michalis P. Stamatogiannis, et al. · International Journal of Finance & Economics (2026) | TGRS Research Map | TGRS