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Risk hedging properties of infrastructure: a quantile regression approach

Author

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  • Surbhi Gupta
  • Anil K. Sharma

Abstract

Purpose - This paper aims to examine the hedge, diversifier and safe haven properties of the global listed infrastructure sector and subsector indices against two traditional asset classes, stocks and bonds, and four alternative asset classes, including commodities, real estate, private equity and hedge funds during extreme negative stock market movements. Design/methodology/approach - Using dynamic conditional correlation and quantile regression, the authors analyze a data set of 12 indices comprising listed infrastructure and traditional asset classes from 2010 to 2019. Findings - Overall, the findings indicate that listed infrastructure acts as an effective diversifier but not as a strong safe haven or hedge when considered in a multiasset context. With minor exceptions, listed infrastructure cannot be concluded as a safe haven against other asset classes under investigation. Practical implications - The present study has implications for institutional investors looking to incorporate infrastructure in their multiasset portfolios for increased portfolio diversification benefits. Originality/value - Despite the increased influence of infrastructure as an asset class, to the best of the authors’ knowledge, this is the first study to investigate the hedge, safe haven and diversifying properties of infrastructure in a multi-asset context.

Suggested Citation

  • Surbhi Gupta & Anil K. Sharma, 2022. "Risk hedging properties of infrastructure: a quantile regression approach," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 40(2), pages 302-312, November.
  • Handle: RePEc:eme:sefpps:sef-07-2022-0382
    DOI: 10.1108/SEF-07-2022-0382
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