How Seattle’s New Machine Learning ETF Is Shaping Long-Term Investment

Seattle Firm Euclidean Technologies Debuts ETF with Machine Learning for Long-Term Equity Investing

Euclidean Technologies, a Seattle-based firm that manages private hedge funds, is now using machine learning technology to bring its stock strategy to the masses. The firm is now converting its hedge funds into an ETF structure, allowing retail investors to trade the Euclidean Fundamental Value ETF on the NYSE. This move is expected to significantly widen Euclidean’s reach as a boutique asset manager with roughly USD 136 million in assets under management, to a firm attracting investments from a much wider array of investors.

Machine Learning in Equity Investing

Euclidean has been using machine learning technology to find undervalued U.S. stocks for its private hedge funds. However, with the launch of its ETF, the firm is taking its approach to the next level by giving individual investors access to its intelligent stock picking system. Using advanced math and computational techniques to pick stocks is not new, but the difference with machine learning is that it can discover “complex, non-linear relationships in high dimensional data”. According to John Alberg, Euclidean’s co-founder and managing partner, machine learning can offer sound long-term investments and improve on traditional quantitative approaches to equity investing.

How Euclidean Is Using Machine Learning

Euclidean’s approach to machine learning started with testing “sequence-to-sequence” learning several years ago, which is a technique used by natural language processing tools like ChatGPT for quantitative investing. The firm deployed its model in March 2020, and since then, its core fund has outperformed S&P 500 total returns by about 3%. The company is now researching the use of machine learning-based language models to quickly analyze written or spoken language related to company performance, such as SEC filings, earnings transcripts, news articles, analyst reports, and investor presentations.

Expert Opinion

It will be interesting to observe whether Euclidean’s machine-based approach to equities will be successful in the retail ETF space. Critics of the machine learning approach argue that human interpretations and emotional intelligence cannot be replaced by robo-trading bots. Nevertheless, there is growing interest in the use of machine learning and AI in the finance space. With accurate data, good quality algorithms, and powerful computational tools, machine learning could enhance and support successful investments by bringing an added level of objectivity and analysis.

Advice For Investors

In the world of investing, no strategy is perfect, and investors need to make their decisions based on their risk tolerance and long-term goals. However, as technology takes on a more significant role in financial planning, individuals may feel an added pressure to consider these options. Investors should do their research and not base any investment decisions on one factor alone. The individual investor should keep in mind that exposure to multiple asset classes, including growth, value, and foreign stocks, may provide the necessary diversification their portfolio needs.