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Our ability to incorporate ESG factors in the evaluation of investments is continually improving as company disclosures and data availability are steadily increasing. CC&L is committed to undertaking regular research projects in order to find ways to improve the integration of these factors into our RI activities.

Quantitative Equity Team

The Quantitative Equity Team is committed to ongoing research related to the integration ESG factors into our quantitative model. The following provides a summary of the research undertaken over the last 5 years:

  • In 2015, the Quantitative Equity team undertook their first formal research project to examine the risk and reward prospects for each individual component of ESG (environmental, social, and governance) as well as a composite of all three within our quantitative model. The key findings from the research concluded at that time, that there was an overlap between ESG scores and the existing alpha and risk factors in the quantitative model. For example, high ESG stocks tended to be large cap stocks (likely because these companies are under pressure to conform to higher standards and also have the resources and capacity to do so) and stocks with low volatility (aside from being large cap, tended to focus on long-term goals and transparency of management). A relationship was also found between ESG scores and sector classification. For example, energy stocks tend to have lower environmental scores.

    While each of the ESG pillars and the composite did predict returns, the explanatory power of these factors was very low in-context of the model’s existing alpha and risk factors. In addition, the data quality and availability at the time was quite poor. As a result, we concluded that the model implicitly captures ESG factors and there was little remaining value to incorporating the factors into our model.

  • In 2018, in conjunction with the CC&L ESG Committee, the Quantitative Equity Team undertook a project to review the quality of the available data and methodologies around measuring ESG risks. This was spurred by our view that ESG data coverage had increased and data quality had improved since our last review in 2015 and therefore, a further project was initiated to re-evaluate the potential benefit of using this data for CC&L’s investment processes. The data review was completed in 2018 and the evaluation of the impact on our model was completed in late 2019. The results from this project indicated an improvement in the data and showed a modest improvement in predictive risk forecasts. The team incorporated E, S, and G rankings as a systematic risk factor, as well as predictors of stock-specific risk, in the quantitative investment process in the summer of 2020.

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