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FORWARD THINKING | ARTICLE – 4 Min

Measuring the impact of climate change on equity risk and portfolio choice

In this article:

    This article is part of our series on current academic research into a range of sustainable investment topics. The papers discussed were presented at the latest annual GRASFI conference.  


    Compelling academic papers

    The Global Research Alliance for Sustainable Finance and Investment is a collaboration of universities committed to producing high-quality interdisciplinary research and teaching curricula on sustainable finance and investment. In this series, we highlight compelling papers presented at the latest GRASFI conference, with a comment from a ‘practitioner’ at BNP Paribas Asset Management (see below).

    As the sustainable investor for a changing world, BNP Paribas Asset Management (BNPP AM) sponsors GRASFI’s efforts to bring academic rigour to the challenges of sustainable finance and investment. Through its sponsorship, BNPP AM is able to access leading academic research into sustainable finance and investment, helping to inform the broader debate. Our goal is to share these reflections with clients and the industry. Visit the GRASFI Conference website.  


    Understanding the impact

    Investors worldwide are trying to understand the impact of climate change on their portfolios. The challenge is particularly acute for investors with extended investment horizons such as pension funds.

    Three authors[1] from Rotterdam School of Management, Erasmus University, have developed a novel framework to allow this type of investor to assess the impact of physical climate risks on long-horizon equity risk returns and make optimal portfolio choices.

    In their paper Climate Change and Long-Horizon Portfolio Choice: Combining Insights from Theory and Empirics, they deploy Bayesian mathematics and the temperature long-run risk (LRR-T) model proposed by Bansal, Kiku, and Ochoa in 2019.

    Their research includes three actionable insights: 

    • The LRR-T model shows stock markets to be riskier over longer horizons. Climate-induced disasters will reduce the mean reversion in returns over time because climate disasters tend to cluster, with disasters following disasters in times of high temperatures. This gives equity markets no time to recover from negative realised returns. Meanwhile, the estimation risk rises, increasing modelled return variance.
    • Investors following the LRR-T will expect the equity risk premium to increase after a climate disaster because the disasters cause a persistent negative shock to risk-free rates. However, the impact on market returns is transitory.
    • The authors say the optimal portfolio choice for LRR-T investors with an investment horizon of 25 years would be investing about 15 percentage points less in the market than one who believes in the original LRR model proposed by Bansal and Yaron in 2004. That model ignores the potential impact of climate change on long-term returns. 

    The authors note that regulators are increasingly demanding that financial institutions quantify their exposure to climate risks. Moves include the IORP II directive from the European Union, which requires that workplace pension schemes across the bloc — which manage more than EUR 2.5 trillion — take long-term issues such as climate change into account and have regular risk assessments.

    Grappling with the unprecedented

    Yet they comment: “Investors struggle to fully grasp the potential impact of climate change on the value of their portfolio and are searching for approaches to quantify these risks.”

    They say much of the research centres on the impact on current asset prices, while fewer look at more extended holding periods: “These long-term effects are difficult to measure due to three key problems: parameter uncertainty, data unavailability, and peso problems.”

    The ‘peso problem’, first popularised by economist Milton Friedman, is the difficulty in assessing the value of assets that could be impacted by an unprecedented or infrequent, but high-impactevent such as a rapid devaluation of the Mexican peso.

    As an illustration, they quote US economist Robert Stambaugh who said when we “expand the horizon to the next several decades, the possible effects of global warming range from negligible to catastrophic.”

    Adding in probabilities

    To provide insight amid such uncertainty, the authors turn to Bayesian mathematics, a flexible and powerful branch of statistics that allows probabilities to be adjusted as new information emerges.

    Historical data about the impact of climate change is limited, which is exactly why using Bayesian statistical tools can work well. They make it possible to include more information than just historical market data. Bayesian methods can also account for uncertainty around the estimated impact of climate change on financial markets.

    Furthermore, information can be extracted from the LRR-T model by seeing how investor concerns over climate change impact current asset prices.

    The authors say their work tackles a long-standing issue when assessing the impact of climate change on future returns: “We provide a concrete approach to deal with the widely shared concern that using historical data to study portfolio allocation has significant limitations in light of the uncertain long-term effects of climate change not present in the data.”

    Existing historical data, they add, may not be informative because the frequency and economic impact of climate-induced disasters is likely to change.

    However, investors do not have to accept the model as developed by the three authors. Instead, their model allows investors to decide for themselves the weighting of historical data versus that from models —and to see how that changes predicted returns. 


    “All investors are intimately aware of the prospectus disclaimer: ‘past performance is not a guarantee of future results.’ Never before has this statement been truer than today given the host of unprecedented secular changes acting on markets, including climate change. Embedding more forward-looking assessments into quantitative risk analysis is likely to be a central project for the next phase in the evolution of our industry. The authors of this report make an important contribution to this emerging discipline,” said Alex Bernhardt, Global Head of Sustainability Research at BNP Paribas Asset Management.


    [1] Mathijs Cosemans, Xander Hut and Mathijs van Dijk; also see www.rsm.nl/ 

    Disclaimer

    Please note that articles may contain technical language. For this reason, they may not be suitable for readers without professional investment experience. Any views expressed here are those of the author as of the date of publication, are based on available information, and are subject to change without notice. Individual portfolio management teams may hold different views and may take different investment decisions for different clients. This document does not constitute investment advice. The value of investments and the income they generate may go down as well as up and it is possible that investors will not recover their initial outlay. Past performance is no guarantee for future returns. Investing in emerging markets, or specialised or restricted sectors is likely to be subject to a higher-than-average volatility due to a high degree of concentration, greater uncertainty because less information is available, there is less liquidity or due to greater sensitivity to changes in market conditions (social, political and economic conditions). Some emerging markets offer less security than the majority of international developed markets. For this reason, services for portfolio transactions, liquidation and conservation on behalf of funds invested in emerging markets may carry greater risk.

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