Kaiju ETF Leads The Charge On Transparency, Responsible AI Ahead Of Looming Regulations

In October, President Biden issued an executive order on the safe, secure and trustworthy use of artificial intelligence. The executive order laid out a set of basic safety and security standards as companies develop new AI capabilities, emphasizing transparency and accountability. While the set of directives addressed the need for clear standards and guidelines on using AI in healthcare, education and across the public sector, there was at least one notable industry not directly addressed by the executive order: investment management. 

An AI act was also approved in the European Union (EU) in December and could come into effect by 2025 in the U.S.. The current draft includes some broad guidance on which regulatory authorities should be responsible for creating and enforcing AI safety standards for financial institutions and services. However, there are still no specific rules or framework for addressing some of the potential issues that can come with the use of AI in finance. 

Kaiju, the maker of the AI-powered Buy the Dip ETF DIP with a 2023 return of +9.76% based on NAV, has been leading the charge on the responsible use of AI in finance to confront the ethical issues that come with it while showcasing what it's capable of.

Performance data quoted represents past performance and is no guarantee of future results. Investment return and principal value of an investment will fluctuate so that an investor's shares, when redeemed, may be worth more or less than the original cost. Current performance may be lower or higher than the original cost. For the most recent standardized and month-end performance, visit the fund's website at www.dipetf.com.

Investors Can't Make Informed Decisions On AI Without Transparency

One of the key challenges with machine learning in finance is the lack of transparency. This is especially poignant with Black Box AI Systems, which are given few, if any, rules and controls and are told to produce a certain outcome – like, for example, "create a trading strategy with a positive expectancy." The result is what is called the "Black Box" problem.

When developers are asked for the reasoning behind their systems' trades, they can tell investors which inputs the system is considering but they cannot tell them exactly how the system made that decision. It's as though they are looking at a lump of ingredients and the meal the ingredients have been made into, but they cannot watch nor describe the transformation.  

But for the investors who are considering buying shares of that AI-driven ETF, those details matter. 

Without explainability, how do you know whether the AI's decision-making is sound? How can you make an informed decision about whether the fund aligns with your investment goals or risk tolerance level if the ETF maker can't really explain how the AI works?

Another issue that can come with this emerging tech is the lack of understanding about what it can and can't do on the financial institution's part. 

While AI can mimic certain aspects of human intelligence, it doesn't yet possess all the reasoning and intuitive intelligence of a human financial advisor. As a predictive tool, for example, it can be surprisingly accurate at making short-term predictions on a narrow scope, but it's not yet powerful enough to make long-term forecasts or account for nuances that would be fairly intuitive to humans. 

"Black box systems that don't take anything into consideration are potentially dangerous because [AI is] not sentient. [It doesn't] have a broad understanding of context in the market," Kaiju CEO Ryan Pannell explained in an interview with Benzinga. "So it's really up to the human portfolio manager to apply some guardrails and keep everybody safe."

You can train an AI to detect trends in large volumes of market data, but it doesn't yet have the capacity to understand the significance of those trends or what decisions to make in response to them – unless a human is there to instruct it. 

Kaiju ETF Advisors Says Responsible Use Of AI Is Key To Gaining Investor Trust

That's where Kaiju sets itself apart with its Buy the Dip ETF. "We're not using black box systems," Pannell said in a TD Ameritrade interview. "So these things aren't just going to run off and invest crazily in whatever they want. They're working within a specific investment ideology framework that we've established."

The AI behind Kaiju's DIP ETF is guided by a classic buy-the-dip strategy. The quantitative strategy relies on short-term pattern recognition and crunching massive volumes of data, two things AI is really good at. The team of developers behind the AI has trained it to identify stocks that are trading temporarily lower than expected based on over 25 quantitative factors.

It's not being tasked with making long-term market predictions, something that would require an understanding of nuance and context AI doesn't currently possess. It's not being tasked with evaluating sentiment, or other qualitative factors that AI still often isn't as good at measuring as humans. 

Moreover, it's following a strategy that most investors already understand: buy stocks that are trading lower than they should be and sell them when they return back up to the correct price. It's just designed to do it faster and more efficiently than a human. 

After sifting through terabytes of data in a fraction of a second and performing over 2 billion discrete examinations, it can spit out a list of every dip it found across the entire market along with recommended entry and exit points for the trades that the ETF's human fund manager can then execute. 

For Kaiju, the DIP ETF represents the ETF maker's commitment to responsible AI. The fund's design is meant to account for the limitations of the technology and put in guardrails to make sure it's doing what it's supposed to be doing. 

Featured photo by Kevin Ku on Unsplash.

This post contains sponsored content. This content is for informational purposes only and is not intended to be investing advice.

Investors should consider the investment objectives, risks, charges and expenses carefully before investing. For a prospectus or summary prospectus with this and other information about the Fund, please call (800) 617-0004 or visit our website at www.dipetf.com. Read the prospectus or summary prospectus carefully before investing.

The Fund is distributed by Quasar Distributors, LLC. Exchange Traded Concepts, LLC (the "Adviser") serves as the Fund's investment adviser. Kaiju ETF Advisors (the "Sub-Adviser") serves as the Fund's investment sub-adviser.

Investing involves risk, including loss of principal. The Fund is subject to numerous risks including but not limited to: Equity Risk, Large Cap Risk, Management Risk, and Trading Risk. The Fund is actively managed and may not meet its investment objective based on the Sub-Adviser's success or failure to implement investment strategies for the Fund. The Fund's principal investment strategies are dependent on the Sub-Adviser's understanding of artificial intelligence. The Fund relies heavily on a proprietary artificial intelligence selection model as well as data and information supplied by third parties that are utilized by such a model. Specifically, the Fund relies on the Kaiju Algorithm to implement its principal investment strategies. To the extent the model does not perform as designed or as intended, the Fund's strategy may not be successfully implemented and the Fund may lose value. A "value" style of investing could produce poor performance results relative to other funds, even in a rising market, if the methodology used by the Fund to determine a company's "value" or prospects for exceeding earnings expectations or market conditions is wrong. In addition, "value stocks" can continue to be undervalued by the market for long periods of time. The Fund is expected to actively and frequently trade securities or other instruments in its portfolio to carry out its investment strategies. A high portfolio turnover rate increases transaction costs, which may increase the Fund's expenses. Frequent trading may also cause adverse tax consequences for investors in the Fund due to an increase in short-term capital gains. The fund is new, with a limited operating history.