Thèmes , Isabelle Cabie , ISR

In-depth quantitative analysis

By Isabelle Cabie, Global Head of SRI, and Tanguy Cornet, Deputy Head of Quantitative Equity Management, Candriam Investors Group.

Combining sustainable & responsible investment with quantitative strategies is a sure means of capturing the alpha from these two different yet complementary approaches. Such a combination represents a major innovation for SRI in terms both of potential performance and of risk diversification.

Sustainable and Responsible Investment (SRI) extends largely beyond ethics: we really do have to see it as a new vision of an ensemble of factors capable of influencing a company’s economic performance. In this, it is complementary to the traditional, purely financial, approach. SRI, following an analysis of the impacts of a company’s environmental, social and governmental (ESG) practices, can be used to identify new levels of performance and to detect certain risk factors that are little taken into account by traditional analysis or quite simply ignored by it. Consequently, the incorporation of SRI analysis and quantitative strategies into the stock selection process can result in stronger portfolios with an enhanced performance potential, with the quantitative part enabling objective exploitation of the investment opportunities provided by the ESG selection.

Twofold ESG analysis

In practice, the process can be split into two parts.

SRI selection

The first consists in defining the SRI investment universe. Here, for each economic sector, the 35% of corporates scoring highest from an ESG standpoint are selected. From a macro point of view, this entails assessing the exposure of the companies’ activities to the major global trends in terms of sustainability. A given business model, for example, will be queried on its ability to meet challenges such as climate change, the exhaustion of natural resources, changes in demographics, health and well-being, and even interconnectivity1.

This macro analysis is complemented by micro analysis, the latter seeking to determine a company’s ability to manage the risks and benefits from the opportunities deriving from interactions with stakeholders in their sector of activity. We will analyse, for example, the firm’s HR management policy not only internally but also as regards their subcontractors. For, as the Rana Plaza (Bangladesh) incident reminded us, a negligent attitude towards stakeholders at production-chain level can prove costly to a company.

Subsequent to the micro and macro analysis, handled by a unique database in which are stocked data accumulated from almost 10 years of experience, companies can be graded and ranked in such a way as to compile, for each sector, a Best-in-Class SRI universe. The latter, incidentally, will include only those firms that also meet two other conditions: (a) compliance with the ten principles of the UN Global Compact covering human rights, labour rights, protection of the environment and anti-corruption; and (b) avoidance of controversial activities such as those represented by the arms, tobacco, gambling and alcohol industries.

Quantitative rigour …

Having thus defined the market index for each sector and considered the universe of companies that best satisfy ESG criteria, the second stage consists in filtering this SRI universe through our quantitative analysis models. These models, developed in-house and tested on an ongoing annual basis, include over 150 factors grouped into 10 alpha engines that test aspects such as valuation, growth, quality indicators and even technical indicators.

As is the case during the SRI analysis process, the quantitative analysis models are adapted to each economic sector. It is our firm belief that such a sector-based approach generates specific major advantages. It provides, on the one hand, in-depth knowledge of the different economic factors that influence each sector, while outlining, on the other, the various risks equated with model failure. Overall, however, the aim of quantitative analysis is to identify alpha-generating stocks under differing market circumstances rather than to detect "absolute" winners. This "all-weather" approach also helps to make portfolios more robust.

In addition, quantitative modelling is the ideal way of coping with the information overload to which investors are exposed. Too much information complicates the search for valid performance factors, as it may lead to investor reactions based on very short-term views and therefore to investors taking decisions that are emotionally fuelled or unconsciously biased.

Securing successful SRI

Today’s ESG strategies are a far cry from the original strategies, which were based on a single criterion, viz., the exclusion of controversial sectors. At the moment, most SRI approaches are "positive" in the sense that, for each universe, region or sector under consideration, only the most sustainable companies count. This combination of SRI and quantitative strategies can be used to capture the alpha from two different albeit complementary approaches. A prime example of innovative sustainable investment, which is constantly evolving, as even its logic makes it always want to include, as far as possible, all the factors that add value to a company in the long term.

Sustainable investment, following analysis of the impacts of a company’s environmental, social and governance practices, can be used to identify new levels of performance and to detect certain risk factors ignored by traditional analysis.
As regards quantitative analysis, the sector-based approach generates specific major advantages, in particular the in-depth knowledge of the different economic factors that influence each sector as well as the diversified risks equated with model failure.
Through the diversity of the factors examined, our "all-weather" approach has been especially designed to generate alpha under different market conditions.

(1)Interconnectivity is not quite the same thing as interconnection or interdependence. It is a term used particularly in biology, network theory and ecology. It is used here to provide a better understanding of the development of the physical and virtual mobility that helps eliminate distance and bring together communities and markets. Examples are activities beneficial not only to the transport of goods and persons but also of data, and other activities boosted by the new technologies.