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Climate risk and investment in equities in Europe: a Panel SVAR approach

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  • Andrea Cipollini
  • Fabio Parla

Abstract

In this study, we use data on European stocks to construct a green-minus-brown portfolio hedging climate risk and to evaluate its performance in terms of cumulative expected and unexpected returns. More specifically, we estimate a Structural Panel VAR fitted to one month return and realized volatility computed for 40 constituents of a green portfolio (i.e., the low carbon emission portfolio monitored by Refinitiv) and for 41 constituents of a brown portfolio (underlying the Oil&Gas and Utilities industry sectors of the STOXX Europe 600). The common shocks underlying the cross-sectional averages, interpreted as portfolio shocks, are retrieved in a first stage of the analysis and they are used to control for cross-sectional dependence. We compute the historical decomposition (for cumulative returns) in a second stage of the analysis and we find, in line with P´astor, L., Stambaugh, R. F., & Taylor, L. A. (2022). Dissecting green returns. Journal of Financial Economics, 146 (2), 403–424, an out-performance of the expected component of the brown portfolio relative to the one for the green portfolio, and an out-performance of the green portfolio when we turn our focus on the unexpected component. We also extend the analysis of P´astor et al. (2022), assessing, for the top 5 constituents of the green portfolio (e.g., those which are found to have the worst performance in terms of expected return), the role played by idiosyncratic shocks in shaping their out-performance in terms of unexpected component. Finally, after exploiting the non-gaussian time series properties of the financial time series considered for the purpose of statistical identification, we are able to interpret ex post the idiosyncratic shocks in terms of financial leverage and risk aversion.

Suggested Citation

  • Andrea Cipollini & Fabio Parla, 2023. "Climate risk and investment in equities in Europe: a Panel SVAR approach," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0093, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    • Handle: RePEc:mod:wcefin:0093
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    References listed on IDEAS

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    1. Ambrogio Cesa-Bianchi & M Hashem Pesaran & Alessandro Rebucci & Stijn Van Nieuwerburgh, 2020. "Uncertainty and Economic Activity: A Multicountry Perspective," The Review of Financial Studies, Society for Financial Studies, vol. 33(8), pages 3393-3445.
    2. Bua, Giovanna & Kapp, Daniel & Ramella, Federico & Rognone, Lavinia, 2022. "Transition versus physical climate risk pricing in European financial markets: a text-based approach," Working Paper Series 2677, European Central Bank.
    3. Pástor, Ľuboš & Stambaugh, Robert F. & Taylor, Lucian A., 2021. "Sustainable investing in equilibrium," Journal of Financial Economics, Elsevier, vol. 142(2), pages 550-571.
    4. Ambrogio Cesa-Bianchi & Andrea Ferrero, 2021. "The Transmission of Keynesian Supply Shocks," Discussion Papers 2116, Centre for Macroeconomics (CFM).
    5. Bolton, Patrick & Kacperczyk, Marcin, 2021. "Do investors care about carbon risk?," Journal of Financial Economics, Elsevier, vol. 142(2), pages 517-549.
    6. Ludvigson, Sydney C. & Ng, Serena, 2007. "The empirical risk-return relation: A factor analysis approach," Journal of Financial Economics, Elsevier, vol. 83(1), pages 171-222, January.
    7. Pástor, Ľuboš & Stambaugh, Robert F. & Taylor, Lucian A., 2022. "Dissecting green returns," Journal of Financial Economics, Elsevier, vol. 146(2), pages 403-424.
    8. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    9. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
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    More about this item

    Keywords

    Climate risk; green and brown portfolios; portfolio shocks; Panel VAR;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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