Artificial intelligence is increasingly being used to analyze markets, generate investment signals, and support portfolio decisions. FINQ is pursuing a more ambitious application: placing AI at the center of the investment process itself, with algorithms responsible for ranking stocks, selecting holdings, and determining portfolio weights.
The asset management company reported that its two AI-managed exchange-traded funds had significantly outperformed the S&P 500 since their February 5, 2026 inception. As of September 30, 2026, FINQ’s dollar-neutral ETF, AINT, had returned 41.56%, while its long-only fund, AIUP, had returned 32.66%. The S&P 500 returned 10.96% over the same period, according to the company’s reported figures.
The results place FINQ among the companies seeking to demonstrate that artificial intelligence can do more than assist traditional investment managers. Its approach is built around autonomous portfolio management, with the system continuously evaluating market information and adjusting investments according to its rankings.
Two Strategies, One AI Framework
FINQ’s funds approach the market differently, despite relying on the same underlying investment philosophy.
The FINQ FIRST U.S. Large Cap AI-Managed U.S. Equity ETF (AIUP) follows a long-only strategy, investing in U.S. large-cap equities selected and weighted by the company’s AI framework. The goal is to maintain exposure to highly ranked companies while adapting the portfolio as market conditions change.
FINQ reports that AIUP outperformed the S&P 500 at every month-end since its inception. Its reported return of 32.66% exceeded the benchmark’s 10.96% by 21.70 percentage points.
AINT, the FINQ Dollar Neutral U.S. Large Cap AI-Managed U.S. Equity ETF, takes a different approach. The fund buys stocks that rank highly in its model while selling short those ranked lowest. This structure is designed to capture differences in the relative performance of companies rather than relying exclusively on the broader market rising.
As of September 30, 2026, AINT had returned 41.56% since inception, outperforming the S&P 500 by 30.60 percentage points, according to FINQ’s figures. FINQ said the fund had outperformed the benchmark at every month-end except its first month of trading.
The distinction matters because the funds are not simply interchangeable products carrying different names. AIUP provides long-only equity exposure, while AINT uses long and short positions to implement a relative-ranking strategy.
What Makes FINQ’s Approach Different?
Traditional active managers rely on combinations of financial analysis, economic forecasts, company research, and professional judgment. Quantitative funds also use algorithms, but FINQ positions its system as an autonomous framework that evaluates index constituents and makes portfolio decisions without discretionary human stock selection.
According to the company, its proprietary technology systematically analyzes financial and market data for index participants in real time. The system ranks companies, selects securities, and adjusts portfolio weights as conditions evolve.
That process is intended to help the funds respond to changing information at a scale and speed that would be difficult to replicate through conventional manual analysis. However, the distinction between automation and investment performance remains important: a system can process information quickly without necessarily interpreting every market development correctly.
FINQ describes AIUP and AINT as the first SEC-registered ETFs in the United States to be fully managed by artificial intelligence. The company launched both products on NYSE Arca in February 2026.
“These results demonstrate the strength and consistency of our AI framework during dynamic market environments,” said Eldad Tamir, founder and CEO of FINQ. “I believe autonomous investing will continue to reshape asset management, and the performance of AIUP and AINT reflects the growing ability of AI to adapt, identify opportunities, and respond to market changes at scale.”
Early Results Are Not a Long-Term Verdict
The performance figures provide an encouraging early data point for FINQ, but the measurement period is still relatively short. Both funds began trading in February 2026, meaning their reported records cover less than eight months.
That limitation is especially relevant when evaluating an investment strategy that claims to adapt to different market environments. A model may perform well under certain conditions and struggle when leadership shifts, volatility increases, or correlations between stocks change.
AINT also introduces short-selling exposure, which can create risks that differ from those of a long-only equity fund. Neither strategy’s reported returns establish that the same performance will persist through a full market cycle.
FINQ’s next challenge is therefore to demonstrate that its approach can sustain its results over a longer period, including less favorable market conditions.
For investors, the September 30 figures offer a snapshot of how the company’s autonomous investing model has performed since launch. They do not guarantee future returns. Investment values fluctuate, and investors may receive less than their original investment when they sell their shares. Current performance may also differ from the figures reported here.
If FINQ can continue to produce competitive results while demonstrating resilience across market cycles, its ETFs could strengthen the case for AI as a portfolio manager rather than merely an analytical tool. For now, the early numbers make the company’s experiment worth watching.
This article was published as a press release by the author under HackerNoon’s Business Blogging program.