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Unveiling asymmetric return spillovers with portfolio implications among Indian stock sectors during Covid-19 pandemic

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  • Mishra, Aswini Kumar
  • Anand K, Kamesh
  • Venkatasai Kappagantula, Akhil

Abstract

This paper aims to provide a systematic inquiry into the return spillover dynamics between a network of Indian sectoral indices during the pre- and post-pandemic periods. To analyze the same, this paper uses the asymmetric time-varying parameter vector autoregressions (TVP-VAR) framework. Furthermore, in the spirit of Broadstock et al. (2020), we perform dynamic portfolio exercises based on common hedging techniques and the minimum connectedness portfolio approach to determine what better captures asymmetry. Our daily dataset includes 12 sectoral stocks spanning from January 01, 2017, to May 5, 2023. The findings reveal that negative connectedness dominates throughout the sample period, demonstrating that profit-maximizing agents and risk-averse investors are more likely to react negatively to news. We also show that in the network, the average net transmitters are the banking and other financial service sectors, whereas the net receivers are the information technology, pharmaceutical, and fast-moving consumer goods sectors throughout the period under consideration. Our results show that the minimum connectedness portfolio (MCoP) approach is a very useful method based on Sharpe ratios, as it is either the first or second most profitable among these three competing methods. These results, therefore, yield valuable insights for policymakers and investors.

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  • Mishra, Aswini Kumar & Anand K, Kamesh & Venkatasai Kappagantula, Akhil, 2025. "Unveiling asymmetric return spillovers with portfolio implications among Indian stock sectors during Covid-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 75(PA).
  • Handle: RePEc:eee:ecofin:v:75:y:2025:i:pa:s1062940824002225
    DOI: 10.1016/j.najef.2024.102297
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    More about this item

    Keywords

    COVID-19; TVP-VAR; Asymmetric connectedness; Portfolio management; Hedging effectiveness; India;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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