J.P. Morgan Asset Management (JPMAM) is pleased to announce the launch of JPMorgan Funds – Thematics – Genetic Therapies in Europe, JPMAM’s first actively managed fund which combines both machine learning and active equity insights. The new fund leverages research carried out by UBS Global Wealth Management’s Chief Investment Office (UBS CIO) within its Longer Term Investments framework, and is being distributed by UBS initially.
Genetic therapies represent a once-in-a-generation breakthrough in the world of medicine. These treatments offer the hope of a cure for patients with serious inherited diseases, by modifying genetic information to address the underlying causes of disease. Today they are at an inflection point, moving from the clinic to commercial reality. This should generate high growth rates for companies operating in the space, and could prove highly disruptive for incumbent companies in the pharmaceutical industry if the technology proves to have wider applications. JPMAM’s Genetic Therapies fund provides the opportunity to investors to gain diversified exposure to this new and exciting theme, and can help to hedge the risk of disruption to existing healthcare portfolios.
The fund will be co-managed by Yazann Romahi, Berkan Sesen and Aijaz Hussein. The portfolio management team sit within JPMAM’s Quantitative Beta Strategies (QBS) team, a team that specializes in quantitative portfolio management and are experts in developing innovative machine learning based technology solutions. Several members of the team hold PhD’s in Artificial Intelligence.
The fund has been designed to combine the strength and reach of JPMAM’s proprietary thematic engine, ThemeBot, with the portfolio management and research capabilities of JPMAM’s global equity platform. ThemeBot can efficiently identify stocks exposed to a range of investment themes including genetic therapies.
Using natural language processing, ThemeBot will screen more than 10,000 stocks globally, rapidly analysing hundreds of millions of data sources, such as news articles, company profiles, research notes and regulatory filings to identify stocks with the highest exposure to the theme and generate a high relevance portfolio, accounting for liquidity, market capitalisation and profitability. The portfolio will invest across the market capitalisation spectrum and provide diversified exposure to both innovative pioneers and established healthcare players. ThemeBot dynamically ensures only the most relevant stocks based on textual and revenue metrics are flagged for inclusion in the portfolio.
Once ThemeBot has selected the stocks it thinks are most applicable to the genetic therapies theme, the QBS team will work with experienced industry career analysts from JPMAM’s global equity platform to vet and validate ThemeBot’s output, to ensure stocks most relevant to the theme secure a spot in the portfolio. The portfolio management team will have access to five dedicated healthcare analysts with an average experience of 19 years. Additionally, the portfolio managers will be able to call upon the expertise of JPMAM’s broader equity analyst community, made up of 51 sector specialists.
Yazann Romahi, Chief Investment Officer of Quantitative Beta Strategies at J.P. Morgan Asset Management, said: “In seeking to create data driven portfolios which brings together human and artificial intelligence, we’re able to offer investors thematic solutions which enable them to tap into some of the central investment themes shaping our world today.”
Mark Haefele, Chief Investment Officer at UBS Global Wealth Management, said: “Genetic therapies could develop into a profoundly disruptive technology for the pharmaceutical and biotechnology industry. Positioning portfolios to capture the economic benefits of disruption, while hedging or mitigating its effects on other assets, supports our goal to help our clients protect and grow their wealth over generations.”
George Gatch, CEO, J.P. Morgan Asset Management, said: “We’re delighted to partner with UBS in developing this new fund. We’re deploying our best Artificial Intelligence (AI) and Big Data capabilities combined with our global research expertise for this investment theme. Innovating jointly with our clients is an important priority for us.”
Christian Wiesendanger, Head of Investment Platforms and Solutions at UBS Global Wealth Management, said: “Developing new solutions with our partners is critical to implementing innovative ideas in clients’ portfolios. Machine learning is an exciting new tool for those looking to be at the cutting edge of investment management and will likely play a greater role in the years ahead.”
The fund’s C share class will have a Total Expense Ratio of 56 basis points.
For Funds Society, Madrid