14 July 2020
June 2020 - Leveraging on ESG data and Artificial Intelligence to participate to the climate transition - Systematic Fund Manager's Comments
Launch of the RAM Stable Climate Global Equities Fund
At RAM, ESG data integration in our systematic equity selection process has been in place for several years already. We now take this process further. As the climate change emergency continues to grow, we are convinced of our role as an asset manager to participate to the climate transition and provide investors with a differentiated solution to low-carbon investing. Thanks to tremendous advances made on our Machine Learning infrastructure, we have built a robust and active strategy with strong ESG standards, without compromising performance.
Intersection of fundamental financial and ESG data
We strongly believe the capture of persistence inefficiencies in the equity market resides in the interdependence between sustainability, return and risk characteristics. Our systematic approach takes a multi-dimensional angle to deliver “sustainable alpha”, leveraging on a myriad of ESG and non-ESG data sources to identify the most attractive risk-reward opportunities in each industry.
RAM AI’s proprietary ESG
ESG data sources we have been progressively integrating into our investment process over the past years carry value-added information from structured and unstructured data. Perfectly aware of the fact that more than three-quarter of new dataset relates to unstructured data, we have developed a state-of-the-art technique to extract information from finance text (i.e. news transcripts, earnings reports, etc) and transform them into quantitative “model friendly” features.
Natural Language Processing (NLP) remedying to the low frequency of ESG data
More conventional climate and ESG related data are at a low frequency and data providers would typically take days or weeks to react, while automatically analysing news flow helps us to identify the latest ESG related issues on companies and assess their wider impact. It is commonly accepted that real-world events reflected within unstructured data, e.g. financial news, earning calls, transcripts, financial reports, social media, etc, have a certain relationship to markets. NLP enables us to integrate inputs from these unstructured and qualitative data sources into our quantitative models. These inputs, which are complementary to our existing quantitative/structured data from analysts’ revisions, enrich the information set that our quantitative models consume.
On top of that, from the investment universe pre-processing perspective, NLP brings an “immediate” flag of controversies and ultimately a rapid exclusion of companies with strong negative ESG news.
Deep Learning models to address the multi-dimensionality problem
The important developments on the Machine Learning infrastructure permits us to process high dimensional data to make informed predictions, simultaneously integrating information across traditional fundamental financial, ESG and alternative data. We use an ensemble approach, consisting of a dozen of Machine Learning models with optimized hyperparameters. We regard Machine Learning techniques as a generalisation of traditional data processing techniques, and our research efforts are equally focused on testing models and controlling them by making sure they generalise and provide tangible results.
Compensating the portfolio carbon emissions by carbon certificates
In the RAM Stable Climate Global Equities Fund, carbon emissions of the portfolio (much lower than those of MSCI World Index) are compensated with carbon certificates issued through the Clean Development Mechanism of the UN. The projects targeted are biomass projects, which have a clear measurable impact on the environment and an auditing process at multiple levels. The cost of these carbon certificates is fully endorsed by RAM AI and not the Fund. In that way, we offer our investors a “pure” approach participating to the climate transition phase.
Further ESG integration across RAM AI’s equity product range
RAM AI’s further ESG data integration is being progressively deployed through our equity product range. We view this process as a continuation of the research efforts entertained over the last 5 years and the commitment and long-term alignment towards the SDGs. The cross-fertilisation of ideas within the RAM research team will lead to more ESG data integration and NLP techniques across the RAM product range to improve the alpha prediction.
RAM Emerging Markets Equities – Improved ESG rating with higher alpha stability
We have brought a sustainable alpha optimization layer to our Emerging Markets equities strategy, which gives a preference in the selection to companies with both high alpha and attractive sustainability. The additional sources of data relate to Agency ESG ratings and News Flow. The process of integrating the sustainability dimension into our alpha makes it more stable, and has the following positive impact on the Fund’s profile:
- More sustainable All-Cap selection
- Lower turnover and trading costs
- Higher expected net alpha
- Reduced active risk versus market-cap based benchmarks
As a result, the MSCI ESG rating of the portfolio is improved from BB to A (vs BB for MSCI Emerging Markets Index).
This document has been drawn up for information purposes only. It is neither an offer nor an invitation to buy or sell the investment products mentioned herein and may not be interpreted as an investment advisory service. It is not intended to be distributed, published or used in a jurisdiction where such distribution, publication or use is prohibited, and is not intended for any person or entity to whom or to which it would be illegal to address such a document. In particular, the products mentioned herein are not offered for sale in the United States or its territories and possessions, nor to any US person (citizens or residents of the United States of America). The opinions expressed herein do not take into account each customer’s individual situation, objectives or needs. Customers should form their own opinion about any security or financial instrument mentioned in this document. Prior to any transaction, customers should check whether it is suited to their personal situation and analyse the specific risks incurred, especially financial, legal and tax risks, and consult professional advisers if necessary. The information and analyses contained in this document are based on sources deemed to be reliable. However, RAM AI Group cannot guarantee that said information and analyses are up-to-date, accurate or exhaustive, and accepts no liability for any loss or damage that may result from their use. All information and assessments are subject to change without notice. Investors are advised to base their decision whether or not to invest in fund units on the most recent reports and prospectuses. These contain further information on the products concerned. The value of units and income thereon may rise or fall and is in no way guaranteed. The price of the financial products mentioned in this document may fluctuate and drop both suddenly and sharply, and it is even possible that all money invested may be lost. If requested, RAM AI Group will provide customers with more detailed information on the risks attached to specific investments. Exchange rate variations may also cause the value of an investment to rise or fall. Whether real or simulated, past performance is not necessarily a reliable guide to future performance. The prospectus, key investor information document, articles of association and financial reports are available free of charge from the SICAVs’ and management company’s head offices, its representative and distributor in Switzerland, RAM Active Investments S.A., Geneva, and the funds’ representative in the country in which the funds are registered. This marketing document has not been approved by any financial Authority, it is confidential and its total or partial reproduction and distribution are prohibited. Issued in Switzerland by RAM Active Investments S.A. which is authorised and regulated in Switzerland by the Swiss Financial Market Supervisory Authority (FINMA). Issued in the European Union and the EEA by the Management Company RAM Active Investments (Europe) S.A., 51 av. John F. Kennedy L-1855 Luxembourg, Grand Duchy of Luxembourg. The reference to RAM AI Group includes both entities, RAM Active Investments S.A. and RAM Active Investments (Europe) S.A.