In smart beta strategies, ESG factors and scores can be used as a weight in portfolio construction to create excess risk-adjusted returns, reduce downside risk and/or enhance portfolios’ ESG risk profile.

Overview of smart beta strategies

Smart beta investing uses a blend of both passive and active investment disciplines. It weights the constituents of a market-capitalisation index by a factor(s) other than market capitalisation – such as value, dividend yield, momentum, growth, quality or volatility – to outperform the index, lower the downside risk or increase the dividend yield. Some smart beta strategies use these types of data directly, and some use mathematical weighting schemes that can result in similar exposures.

By applying different weights, a portfolio is created that has different characteristics and returns compared to a conventional index weighted by market-capitalisation. For example, a smart beta portfolio weighted by the value factor PE ratio will consist of a higher percentage of lower PE stocks, which will therefore drive its performance. A conventional index, on the other hand, has a natural bias towards companies with a large market capitalisation and therefore its performance is largely dictated by the share price performance of large marketcapitalisation companies.

Portfolio construction methodologies of smart beta products can be grouped into two categories.

Heuristic-based weighting methodologies calculate the weights of securities by using simple, heuristic rules that are applied systematically across all constituents. For example, the weights of each index constituent of a momentum-weighted index are calculated by dividing the stock’s momentum score by the sum of all constituents’ momentum scores. Other popular heuristic based weighting strategies are equal weighting, fundamentals weighting and risk clusters equal weightings.

Optimisation-based weighting methodologies involve complex optimisation techniques to create portfolios maximising return or minimising risk. For example, a lowvolatility weighted index involves forecasting the future volatility of each index constituent and then applying a lower/higher weight to high/low volatility stocks respectively.

Bank J. Safra Sarasin has analysed the relationship between governance indicators and downside risk and utilised their research in their portfolio construction process. To select innovative water solution providers for their “smart water” products, Calvert Investments uses its proprietary research system to identify financially material indicators of water efficiency and water impact among firms in sectors with high water intensity, such as food products, paper or semiconductors.

Managers who integrate an ESG factor into a smart beta portfolio often adjust holdings for other factors, such as the value factor PE ratio mentioned above. In one of these case studies, AXA Investment Managers adjusts the weights of stocks in a global equity universe to increase the exposure to companies with a high profitability, high quality of earnings, low-risk profiles and top ESG scores.

Download report