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Investment Product and Service Launches
J.P. Morgan designs core menu evaluation tool; FTSE Russell launches enhanced Green Revenue Data Model; Franklin Templeton presents goals optimization engine; and more.
J.P. Morgan Designs Core Menu Evaluation Tool
J.P. Morgan Asset Management has announced the launch of the Core Menu Evaluator.
The tool is one of the first designed specifically for defined contribution (DC) plans, allowing users to better understand a plan’s core investments by assessing portfolio composition, risk, performance and fee structure. Users can also utilize the tool to easily customize data and reports to share with plan sponsors.
The Core Menu Evaluator adds to J.P. Morgan’s suite of digital DC tools and resources that allow advisers to review and select the most appropriate qualified default investment alternative (QDIA), assess core menu investments and review pricing for a bundled service via the firm’s newly launched Retirement Plan Tools & Resources landing page.
“We understand that retirement portfolios are only as strong as the investment choices available, and the Core Menu Evaluator has been specifically designed to make it simple for financial professionals to quickly, thoroughly and objectively assess investments,” says Michael Miller, head of Retirement Americas at J.P. Morgan Asset Management. “This new tool builds on our one-stop-shop of digital retirement resources including Target Date Compass and Price Smart, which have been developed to empower better decisions and build stronger retirement plans.”
FTSE Russell Launches Enhanced Green Revenue Data Model
FTSE Russell has launched its enhanced Green Revenues 2.0 Data Model, which measures the green revenue exposure of more than 16,000 listed companies across 48 developed and emerging markets. This represents 98.5% of the total global market value of listed companies.
FTSE Russell’s Green Revenues 2.0 Data Model provides investors with a classification system covering green products and services in 10 sectors, 64 sub-sectors and 133 micro-sectors. A green “tiering” system is also applied to determine net environmental impact based on seven environmental objectives, recognizing that green revenues come in lighter and darker “shades.”
By using three tiers to rank sources of green revenue by “Limited,” “Net Positive” and “Clear and Significant,” FTSE Russell’s Green Revenues data supports a clearer understanding of investors’ “green exposure.” The data model can also be used for a growing number of regulatory reporting needs, including climate performance against Task Force on Climate-related Financial Disclosures (TCFD) requirements and EU Taxonomy regulation. Over a decade of green revenues data is available, dating back to 2008, enabling investors to track a company’s progress in achieving green standards.
“FTSE Russell’s enhanced Green Revenues 2.0 Data Model is a powerful tool that investors can use to quantify a company’s contribution to the green economy in a single percentage of revenue figure,” says Arne Staal, global head of research and product management at FTSE Russell. “A high degree of overlap with the incoming EU Taxonomy will also allow asset managers to demonstrate the proportion of a fund that contributes to the growing and dynamic green economy.”
Franklin Templeton Presents Goals Optimization Engine
Franklin Templeton has introduced its proprietary Goals Optimization Engine, or GOE.
The global offering provides investors with personalized investment paths for their goals and gives financial professionals a scalable way to offer a differentiated investment solution and deepen client relationships. The Engine is built based on 2018 Markowitz Award winning proprietary research that defines investment success by whether or not the investor’s goals are achieved, recommending investment decisions that will help maximize that chance of success. Banks, advisers, financial professionals and defined contribution (DC) plans can leverage the technology to help provide better outcomes to their clients while gaining business efficiencies.
“We are seeing an increased demand for goals-based planning and personalized investment solutions globally, and the application of machine learning is enabling what was previously unimaginable,” says Jed Plafker, EVP, global alliances and new business strategies. “As society generally moves towards digital platforms and technology-based services, GOE is the technology that will enable advisers and financial services firms to deliver personalized, higher value services at greater scale.”
GOE, a patent pending process, combines a proprietary algorithm based on research, detailed capital market expectations, and a set of parameters for each goal provided by the investor. GOE is designed to take these parameters and optimize the asset allocation to maximize the probability of successfully achieving the goal by applying machine learning. This optimization process occurs regularly through the time horizon of the investment and re-allocates assets to increase or decrease risk in the portfolio as needed. GOE will de-risk as the goal target approaches versus reaching for a higher return, with higher risk. GOE can also facilitate decisions across goals with different priorities.
GOE’s open-architecture offering will be delivered through AdvisorEngine, Franklin Templeton’s recently acquired platform. Franklin Templeton is also building relationships with third-party technology companies and financial institutions to enable access around the world. One such relationship is with NextCapital, with whom GOE will be brought to market as part of a discretionary managed advice solution for the DC plan industry.
Natixis Launches Three Active ETFs
Natixis Investment Managers announced its entrance into the semi-transparent exchange-traded fund (ETF) market with the launch of three high conviction, actively managed U.S. equity products.
They represent a new vehicle for existing strategies that are currently available as mutual funds with well-established track records, the firm says.
Effective immediately, clients have access to the following products listed on NYSE Arca, Inc.:
- Natixis U.S. Equity Opportunities ETF (EQOP);
- Natixis Vaughan Nelson Mid Cap ETF (VNMC); and
- Natixis Vaughan Nelson Select ETF (VNSE).
Leveraging the New York Stock Exchange (NYSE)’s Proxy Portfolio Methodology approach, Natixis’s semi-transparent active ETFs disclose proxy portfolios on a daily basis and closely track the actual portfolios’ intraday performance. This structure allows the portfolio managers to shield the identity of stocks on which they are actively trading, while still providing market makers enough information to offer competitive bids and asks on the ETFs. Natixis’ active semi-transparent ETFs give investors access to highly skilled active managers through a tax-efficient and lower-cost vehicle.
The Natixis U.S. Equity Opportunities ETF is a multi-managed, diversified core equity product combining fundamentally driven growth and value managers. Loomis Sayles’ Growth segment is managed by Aziz Hamzaogullari (CIO and founder of the Loomis Sayles Growth Equity Strategies Team), and Harris Associates’ Value segment is managed by Bill Nygren (CIO), Kevin Grant, Colin Hudson, Michael Mangan and Michael Nicolas.
The Natixis Vaughan Nelson Mid Cap ETF takes advantage of temporary information and marketplace inefficiencies in the mid-cap universe to find opportunities to invest in companies at valuations materially below their long-term intrinsic value. The fund invests in companies within the market capitalization range of the Russell Midcap Value Index at the time of purchase. Chris Wallis (CEO & CIO), Chad Fargason and Dennis Alff are the named portfolio managers.
The Natixis Vaughan Nelson Select ETF invests in companies within the market capitalization range of the Russell 3000 Index at time of purchase and seeks long-term capital appreciation. The strategy employs sophisticated, proprietary analysis, valuation and risk management. Managers Chris Wallis and Scott Weber follow a research-intensive process emphasizing balance sheets and cash flow-based projections.You Might Also Like:
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