The Energy Transition Long-Short Equity Index US (ETLS US) is a rules-based alternative index strategy designed to benchmark and capture the potential upside of a transition to a low-carbon economy. This thematic, long-term index offers investors exposure to a universe of US listed clean-energy and fossil-fuel companies. ETLS US is long US clean energy, advanced transportation, and smart grid companies and short US reserve-owning fossil fuel companies.
Energy Transition Long-Short US
Constituents include public companies, whose products and services aim to accelerate the clean-energy transition and reduce the physical, economic, and social risks associated with climate change.
The index goes beyond divestment, shorting companies whose products generate CO2 emissions, which are a main factor contributor to climate change to stranded asset risk.
An alternative index strategy designed to capture long-term return generation from the energy transition.
|Since Inception||3 Months||Year to Date||12 Months||3 Years||5 Years|
|S&P 500 Energy||-6.67%||7.97%||54.64%||54.64%||14.68%||-7.02%|
Net Market Cap
- Long company selection: The Clean Edge universe of U.S.-listed clean energy, advanced transportation, and smart grid and grid infrastructure companies using fundamental quality factors.
- Short company selection: U.S.-listed companies from FFI Solution’s Carbon Underground 200™ (CU200), a list of global publicly traded companies ranked by potential CO2 emissions embedded in their reported oil, gas, and coal reserves. Positions selected and weighted based on a combination of fundamental and carbon-related factors that indicate the degree to which fossil fuel companies are exposed to the risk of stranded assets.
- Long and short components: Adjusted dynamically using proprietary factors from Alpha Vee that measure quality, value and momentum of the component issuers. The net long exposure ranges from 40% to 100% with the short position comprising either 20% or 30% depending on the momentum indicator.
- Reconstitution: Semi-annually
- Rebalancing: Semi-annually
|Number of Stocks||40||20|
|Min Market Cap||$75 Million||$1 Billion|
|Min Avg Daily Volume||$1 Million||$1 Million|
|Net Exposure Range||40% to 100% Net Long|
|Gross Exposure Range||100% to 160%|
|Benchmark||S&P 500 Energy Total Return|
ETLS US Information
Fossil Free Indexes LLC and its third-party data providers and licensors do not guarantee the accuracy, completeness, timeliness or availability of the information contained herein. Nothing in this document shall constitute financial or investment advice, or an offer to buy or sell, or a promotion or recommendation of any security, financial instrument or product or trading strategy.
It is not possible to invest in an a portfolio derived from the Strategy directly. FFI designed and will maintain the Strategy for use as an index in investment strategies managed by the investor or another party. FFI is not an investment adviser, and FFI makes no representation regarding the advisability of investing in any such investment fund or other investment vehicle that is based on the Strategy. A decision to invest in any such investment fund or other investment vehicle based on the Strategy should not be made in reliance on any of the statements set forth here. FFI is not a tax advisor. A tax advisor should be consulted to evaluate the impact of any securities on portfolios and the tax consequences of making any particular investment decision based on the Strategy. Inclusion of a security within the Strategy or index based on the Strategy is not a recommendation by FFI to buy, sell, or hold such security, nor is it considered to be investment advice.
All performance information presented is hypothetical and back-tested. Hypothetical performance does not take into account estimated advisory fees and transaction costs that would apply to any account implementing the index. Actual index performance from live investment portfolios may differ materially from hypothetical returns. There is no substitute for actual returns from a live portfolio. Back-testing is done by retroactively applying a hypothesis to the historical data to obtain returns (scientific method) or finding variables in historical data that correlate to returns and developing a hypothesis from the historical data (data mining) or applying any hypothesis to different time periods until favorable returns are discovered (data mining). Back-tested models are developed with the benefit of hindsight but might not have foresight of the future. Hypothetical performance does not reflect the macroeconomic risks of investing based on the Strategy in a different time period or the financial risk of executing trades in a live portfolio which include the potential market impact on stock prices caused by buying or selling that could cause buy or sell prices to differ from the frictionless trades of the back-tested model. Although the information in the Presentation gives you some idea of the historic risks involved in investing based on the Strategy, PAST HYPOTHETICAL PERFORMANCE IS NOT A GUARANTEE OF FUTURE RETURNS.
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