This thesis explores Environmental, Social, and Governance (ESG) investments within the European Monetary Union (EMU), with the aim of providing insights into how demand for these assets relates to their unique return characteristics, specifically higher moments, and how it is driven by investor preferences and risk aversion. We extend the Six-Factor Fama & French Model by introducing a new factor, Leaders Minus Laggards (LML), which captures the performance differential between ESG leaders and laggards. Optimisation is then performed on a portfolio created using the Fama & French factors plus the LML factor, by incorporating higher moments into the portfolio allocation process and considering 20 different risk aversion levels. Our findings reveal that the allocation to the LML factor increases significantly when higher moments are considered, highlighting the unique characteristics of sustainable investments. Additionally, we demonstrate that more risk-averse investors tend to favour ESG assets, providing an explanation for their growing popularity. This analysis contributes to a deeper understanding of ESG investments, laying the groundwork for future research in this evolving field.

This thesis explores Environmental, Social, and Governance (ESG) investments within the European Monetary Union (EMU), with the aim of providing insights into how demand for these assets relates to their unique return characteristics, specifically higher moments, and how it is driven by investor preferences and risk aversion. We extend the Six-Factor Fama & French Model by introducing a new factor, Leaders Minus Laggards (LML), which captures the performance differential between ESG leaders and laggards. Optimisation is then performed on a portfolio created using the Fama & French factors plus the LML factor, by incorporating higher moments into the portfolio allocation process and considering 20 different risk aversion levels. Our findings reveal that the allocation to the LML factor increases significantly when higher moments are considered, highlighting the unique characteristics of sustainable investments. Additionally, we demonstrate that more risk-averse investors tend to favour ESG assets, providing an explanation for their growing popularity. This analysis contributes to a deeper understanding of ESG investments, laying the groundwork for future research in this evolving field.

ESG Asset Demand and Higher Moments in Asset Allocation: A Seventh Factor for the Fama & French Model

FRANZIN, ALBERTO
2023/2024

Abstract

This thesis explores Environmental, Social, and Governance (ESG) investments within the European Monetary Union (EMU), with the aim of providing insights into how demand for these assets relates to their unique return characteristics, specifically higher moments, and how it is driven by investor preferences and risk aversion. We extend the Six-Factor Fama & French Model by introducing a new factor, Leaders Minus Laggards (LML), which captures the performance differential between ESG leaders and laggards. Optimisation is then performed on a portfolio created using the Fama & French factors plus the LML factor, by incorporating higher moments into the portfolio allocation process and considering 20 different risk aversion levels. Our findings reveal that the allocation to the LML factor increases significantly when higher moments are considered, highlighting the unique characteristics of sustainable investments. Additionally, we demonstrate that more risk-averse investors tend to favour ESG assets, providing an explanation for their growing popularity. This analysis contributes to a deeper understanding of ESG investments, laying the groundwork for future research in this evolving field.
2023
This thesis explores Environmental, Social, and Governance (ESG) investments within the European Monetary Union (EMU), with the aim of providing insights into how demand for these assets relates to their unique return characteristics, specifically higher moments, and how it is driven by investor preferences and risk aversion. We extend the Six-Factor Fama & French Model by introducing a new factor, Leaders Minus Laggards (LML), which captures the performance differential between ESG leaders and laggards. Optimisation is then performed on a portfolio created using the Fama & French factors plus the LML factor, by incorporating higher moments into the portfolio allocation process and considering 20 different risk aversion levels. Our findings reveal that the allocation to the LML factor increases significantly when higher moments are considered, highlighting the unique characteristics of sustainable investments. Additionally, we demonstrate that more risk-averse investors tend to favour ESG assets, providing an explanation for their growing popularity. This analysis contributes to a deeper understanding of ESG investments, laying the groundwork for future research in this evolving field.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14247/24216