Osmosis launched in 2009 and is an award-winning sustainable investment manager headquartered in London. National Pension Funds, State Pension Funds, Insurance Companies, Foundations, Endowments, Family Offices and Banks, are amongst our client roster spanning North America, Continental Europe, Nordics and the UK. The Osmosis Model of Resource Efficiency (MoRE) is a proprietary investment database developed and maintained by the team at Osmosis. The MoRE model allows us to create an objective, sustainable, alpha generating investment factor, through the identification across thirty-two economic sectors of companies who are generating more revenue consuming less resource than their sector peers. Our systematic investment strategies & funds target an improved risk-return profile and importantly deliver significantly reduced environmental footprints to their relative benchmarks.
The MoRE World strategy is designed to outperform MXWO (MSCI Developed World Index). The stocks are systematically selected from 32 industry sectors, developed markets only, each stock chosen for inclusion will be ranked in the top decile of their relative sector based on their MoRE Resource efficiency score. The stocks are then weighted for value based on the economic PE of each company. The portfolio is broadly diversified across sectors excluding financials, has a large cap bias and is consistently over 60 percent more resource efficient than its benchmark.
Key Features and Coverage on RIMES
For this data source, RIMES hosts approximately 936 companies and one index – World Smart Beta. Some of the data items available include:
- Company Items – Adjusted Price, Country Code, Currency Code, Exchange Rate, Investable Factor, Investable Market Value in US Dollars, Investable Shares Outstanding, Investable Weight, Investable Weight in Index (Source), ISIN Code, Sedol Code, Shares Outstanding, Unadjusted Price, etc,
- Index Items – Database Domain Code, Database Symbol, Description, Last Price Date, Gross Index in US Dollars, Net Index in US Dollars, Price Index in US Dollars, etc.