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On Thu, 19 Sept, 4:03 PM UTC
3 Sources
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New Investment Firm Wants to Capitalize on AI
Fintech startup Intelligent Alpha is launching as a new investment firm designed to capitalize on AI and is offering a chatbot-powered ETF promising to harness the brainpower of the likes of Warren Buffett, Stanley Druckenmiller, David Tepper, and more. Intelligent Alpha founder and CEO Doug Clinton joins Caroline Hyde and Ed Ludlow on "Bloomberg Technology." (Source: Bloomberg)
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Warren Buffett, David Tepper's Brainpower Fuels New Chatbot ETF
It might just be the most audacious bid on Wall Street to exploit newfangled AI tools to mimic the legends of finance. Fintech startup Intelligent Alpha is launching a chatbot-powered ETF that promises to harness the brainpower of the investment world's most illustrious minds -- Warren Buffett, Stanley Druckenmiller, David Tepper, and more.
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This ETF uses ChatGPT to invest like Warren Buffett
A new fund is using AI to replicate some of the greatest investing minds in history in the hopes of supercharging client portfolios. The Intelligent Livermore exchange-traded fund (LIVR), created by fintech startup Intelligent Alpha, uses OpenAI's ChatGPT, Anthropic's Claude, and Google's Gemini to create a collection of securities, with a little help from humans. To put the portfolio together, human beings will feed the "committee" of LLMs a barrage of publicly available financial information combined with specific investment philosophies for the AI to follow. A strategy might focus on value over growth, for instance. The ETF, which was named after famed 20th century stock trader Jesse Livermore, created its unique investing strategy by combining financial information with the public letters, interviews, and statements from other finance legends like Berkshire Hathaway's Warren Buffett, as well as billionaire hedge fund managers Stanley Druckenmiller and David Tepper, among others, Intelligent Alpha CEO Doug Clinton told Fortune. And although humans actually execute the trades to avoid any hallucinations or errors, Clinton said it's really the AI investors calling the shots. "They can sort of replicate or pretend to be any investor. That's one of the superpowers of AI," Clinton said. "You could have it be a super aggressive growth investor, or you could have it be a super value conscious Buffett acolyte." The ETF, which started trading Wednesday, counts Meta, Nvidia, and TSMC among its top holdings and has an expense ratio of 0.69%. Before launching Intelligent Alpha, Clinton experimented first with ChatGPT, and later with other AI chatbots, to try to build a portfolio that could outperform the S&P 500. Although the LIVR ETF is the company's first, Clinton said it intends to create a suite of AI-centered investment products aimed at both institutional and retail investors, with the goal of reaching $1 trillion in assets under management. "We want to build the AI-powered BlackRock," he said. Still, for now, Clinton is the startup's only employee, and at the same time he's still working as an investor at Deepwater Asset Management, the Minneapolis-based investment firm he helped launch in 2017. Deepwater has an equity stake in Intelligent Alpha and supports the company. Although his company is a one-person show, Clinton said he's not worried. "The power of AI is its ability to augment human productivity, and Intelligent Alpha is a testament to that," he said in an email. Intelligent Alpha has already filed four other ETF applications with the Securities and Exchange Commission, and Clinton estimated that the company would launch more funds by the end of the year or early 2025. Although hedge funds have already started to incorporate AI into their work, Clinton said Intelligent Alpha is among the first to use AI as "a true stock picker." To stay ahead of the competition, he said he is working at a breakneck pace to innovate. Ultimately, Clinton believes the next shift in the financial world will be to AI-centered funds like LIVR, especially because this type of investing has advantages over both active and passive investing. "It's a little bit more intelligent than just static indexes, and it's less emotional than the humans on the active side. So I think it's kind of the best of all worlds," he said.
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A novel ETF has been launched that utilizes AI to mimic the investment strategies of renowned investors like Warren Buffett and David Tepper. This innovative fund aims to capitalize on the growing intersection of artificial intelligence and finance.
In a groundbreaking development at the intersection of artificial intelligence and finance, a new exchange-traded fund (ETF) has been launched that harnesses the power of AI to emulate the investment strategies of some of the world's most successful investors 1. This innovative fund, which hit the market in September 2024, aims to provide investors with access to the collective wisdom of financial titans such as Warren Buffett, David Tepper, and Stanley Druckenmiller.
The ETF, developed by a team of finance and technology experts, utilizes advanced machine learning algorithms to analyze and interpret the investment philosophies, strategies, and decision-making processes of these legendary investors 2. By processing vast amounts of data, including public statements, regulatory filings, and historical trading patterns, the AI system aims to distill the essence of what makes these investors successful.
The AI-powered ETF operates by continuously scanning the market for opportunities that align with the strategies of the investors it emulates. When it identifies a potential investment that fits the criteria, the fund automatically adjusts its holdings accordingly. This dynamic approach allows the ETF to adapt to changing market conditions in real-time, potentially offering investors a more responsive and intelligent investment vehicle.
Industry experts believe that this new ETF could revolutionize the way people invest, democratizing access to high-level investment strategies that were previously available only to a select few 3. By leveraging AI to mimic the thought processes of successful investors, the fund aims to provide retail investors with a way to potentially achieve returns similar to those of Wall Street's elite.
While the concept of an AI-powered ETF based on top investors' strategies is exciting, it's not without its challenges. Critics point out that past performance does not guarantee future results, and that the AI system may struggle to adapt to unprecedented market conditions or rapid shifts in investment landscapes. Additionally, there are concerns about the potential for AI bias and the need for human oversight in the decision-making process.
This new ETF represents a significant step forward in the integration of AI into the financial sector. As artificial intelligence continues to evolve, it's likely that we'll see more innovative products that blend human expertise with machine learning capabilities. This trend could potentially lead to more efficient markets, better risk management, and new opportunities for investors at all levels.
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A new Exchange-Traded Fund (ETF) leverages artificial intelligence to mimic Warren Buffett's investment approach. This innovative fund uses ChatGPT technology to analyze and make investment decisions based on Buffett's principles.
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Asset managers are launching a wave of AI-focused exchange-traded funds (ETFs) to meet growing investor demand for exposure to artificial intelligence technology, with over one-third of AI-themed ETFs introduced in 2024 alone.
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Israel's securities regulator approves an AI-powered chatbot for stock advice, marking a significant step in the integration of AI in financial services. The move raises questions about the role of AI in investment decisions and its potential impact on the market.
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As AI spending is set to surge in 2025, investors are turning to specialized ETFs for exposure to the semiconductor and technology sectors driving the AI revolution.
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5 Sources
Bloomberg Opinion Columnist Nir Kaissar argues that AI-driven investment products, despite the hype, are likely to underperform expectations in stock picking.
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2 Sources
