The numbers from FINQ’s first quarter of live trading are straightforward. AIUP returned 7.96%. AINT returned 10.65%. The S&P 500 returned 4.57%. Both funds outperformed the index, and no human portfolio manager made a single investment decision behind any of those figures.
FINQ’s two ETFs launched on NYSE Arca on February 5, 2026, and are the first SEC-registered U.S. funds in which artificial intelligence autonomously manages every aspect of portfolio construction, from stock selection through rebalancing. The performance data covers inception through April 30, 2026.
The Two Funds
AIUP, the FINQ FIRST U.S. Large Cap AI-Managed Equity ETF, is a long equity fund. It holds U.S. large-cap stocks selected, weighted, and rebalanced by FINQ’s proprietary AI. Its gross expense ratio is 0.70%.
AINT, the FINQ Dollar Neutral U.S. Large Cap AI-Managed Equity ETF, is a more complex vehicle. It holds long and short positions simultaneously in a dollar-neutral structure, seeking to profit from the relative performance between the securities it buys and those it shorts. It does not rely on the market moving in any particular direction to generate returns. Its gross expense ratio is 1.25%.
FINQ is a U.S. and Israel-based wealth-tech company that built the autonomous AI framework managing both funds. The company’s stated mission is to democratize access to high-end investment products and services, and these two funds represent the most direct expression of that goal to date. Together, they mark the arrival of a genuinely new category of investment product in the U.S. market.
The Performance in Detail
| Fund | Return | S&P 500 Return | NAV | Market Price |
| AIUP | 7.96% | 4.57% | $26.20 | $26.21 |
| AINT | 10.65% | 4.57% | $27.69 | $27.66 |
Beating the S&P 500 by 3.4 percentage points, as AIUP did, is a strong result for any actively managed fund. Beating it by more than six points, as AINT did, is stronger still. Both figures reflect the AI framework operating autonomously across a live market, making every selection and weighting decision without human input.
The funds are also notable for what they represent structurally. These are not model portfolios or simulation results. They are SEC-registered, publicly traded ETFs that have operated in live market conditions from day one. Every return figure in the table above was produced by an autonomous AI system making real investment decisions with real capital. That context makes the outperformance more significant, not less.
FINQ publishes standardized performance data, holdings, and benchmark comparisons on the AIUP and AINT fund pages, ensuring that investors have full visibility into the AI’s portfolio decisions and how those decisions are performing against the benchmark over time.
Why This Launch Matters Beyond the Numbers
The arrival of SEC-registered, AI-managed ETFs on a major U.S. exchange is a structural development for the investment industry, independent of any single quarter’s returns. Active management has historically required human judgment at the center of the process. FINQ has demonstrated that a fully autonomous AI system can satisfy the regulatory requirements for a registered investment vehicle and produce competitive returns doing so.
That changes the conversation around what AI can do in asset management. The question is no longer whether AI can manage a portfolio. It is managing one. The question now is how that management performs across a wider range of market conditions and over a longer time horizon.
What Comes Next for FINQ
“We are happy to lead the next generation of AI-managed investments, with the introduction of our first two ETFs to be followed by many more products and services, creating a leading wealth-management company based on AI,” says Eldad Tamir, founder and CEO of FINQ.
FINQ has entered its first quarter of live trading with results that validate the core premise of its platform: that an autonomous AI system can manage a registered investment vehicle and outperform the broader market doing so. The expansion of that platform is already underway.
