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FINQs AI-Managed ETFs Outperform S&P 500 in First Three Months
On February 5 2026, Israeli asset manager FINQ introduced two exchange‑traded funds that let a proprietary artificial‑intelligence system run the portfolio. Within three months, the funds have already eclipsed the S&P 500 benchmark.
A performance report released on May 4 2026 shows that the FINQ FIRST U.S. Large Cap AI‑Managed Equity ETF (ticker AIUP) returned 15.30 % since inception, compared with a 10.07 % gain for the S&P 500. The FINQ Dollar Neutral U.S. Large Cap AI‑Managed Equity ETF (ticker AINT) posted a 27.13 % return, also outpacing the benchmark.
Both ETFs trade on NYSE Arca and exhibit tight alignment between market price and net asset value (NAV). AIUP closed the day at $28.00 with an NAV of $27.93; AINT closed at $31.78 with an NAV of $31.74.
FINQ’s AI framework is a continuously learning model that ranks, selects, and weights all 500 constituents of the S&P 500 in real time. Rather than relying on periodic rebalancing or human analyst input, the system processes large volumes of financial and market data to adjust exposure as new information arrives.
The two ETFs use the same intelligence layer but apply it differently. AIUP is a long‑only strategy that concentrates on the highest‑ranked large‑cap stocks while maintaining broad index alignment. AINT, by contrast, is a dollar‑neutral long/short strategy that goes long the top‑ranked names and shorts the lowest‑ranked ones, thereby isolating the AI’s relative ranking signal.
The consistency of the results has attracted attention. AIUP has outperformed the S&P 500 at every month‑end since launch, and AINT recovered from a single early month of underperformance to maintain a steady lead thereafter. FINQ’s founder and chief executive officer, Eldad Tamir, said in a statement that the performance “demonstrates the strength and consistency of our AI framework during dynamic market environments” and that autonomous investing will continue to reshape asset management.
While the early track record is notable, FINQ acknowledges that past performance does not guarantee future results. The company has not released a detailed risk profile for the funds, and the performance data covers only the first three months of trading.
The launch of AIUP and AINT represents the first instance of a publicly traded ETF that is managed entirely by an AI system, according to FINQ’s own disclosures. The company claims that its approach removes the interpretive layer that traditional active managers rely on, allowing the AI to respond to market changes in real time.
Investors and analysts will be watching how the funds perform through different macroeconomic regimes, as the AI’s ability to adapt to changing market leadership and sector rotation will be tested over longer horizons.
In summary, FINQ’s AI‑managed ETFs have delivered returns that exceed the S&P 500 benchmark in the early months of operation, with performance data that suggests consistent outperformance rather than a one‑off market timing event. The funds’ alignment with NAV, the dual strategy design, and the company’s public statements all point to a significant experiment in autonomous portfolio construction.
The next steps for the funds will likely include continued monitoring of performance, disclosure of risk metrics, and potential expansion of the AI framework to other asset classes or markets.
A performance report released on May 4 2026 shows that the FINQ FIRST U.S. Large Cap AI‑Managed Equity ETF (ticker AIUP) returned 15.30 % since inception, compared with a 10.07 % gain for the S&P 500. The FINQ Dollar Neutral U.S. Large Cap AI‑Managed Equity ETF (ticker AINT) posted a 27.13 % return, also outpacing the benchmark.
Both ETFs trade on NYSE Arca and exhibit tight alignment between market price and net asset value (NAV). AIUP closed the day at $28.00 with an NAV of $27.93; AINT closed at $31.78 with an NAV of $31.74.
FINQ’s AI framework is a continuously learning model that ranks, selects, and weights all 500 constituents of the S&P 500 in real time. Rather than relying on periodic rebalancing or human analyst input, the system processes large volumes of financial and market data to adjust exposure as new information arrives.
The two ETFs use the same intelligence layer but apply it differently. AIUP is a long‑only strategy that concentrates on the highest‑ranked large‑cap stocks while maintaining broad index alignment. AINT, by contrast, is a dollar‑neutral long/short strategy that goes long the top‑ranked names and shorts the lowest‑ranked ones, thereby isolating the AI’s relative ranking signal.
The consistency of the results has attracted attention. AIUP has outperformed the S&P 500 at every month‑end since launch, and AINT recovered from a single early month of underperformance to maintain a steady lead thereafter. FINQ’s founder and chief executive officer, Eldad Tamir, said in a statement that the performance “demonstrates the strength and consistency of our AI framework during dynamic market environments” and that autonomous investing will continue to reshape asset management.
While the early track record is notable, FINQ acknowledges that past performance does not guarantee future results. The company has not released a detailed risk profile for the funds, and the performance data covers only the first three months of trading.
The launch of AIUP and AINT represents the first instance of a publicly traded ETF that is managed entirely by an AI system, according to FINQ’s own disclosures. The company claims that its approach removes the interpretive layer that traditional active managers rely on, allowing the AI to respond to market changes in real time.
Investors and analysts will be watching how the funds perform through different macroeconomic regimes, as the AI’s ability to adapt to changing market leadership and sector rotation will be tested over longer horizons.
In summary, FINQ’s AI‑managed ETFs have delivered returns that exceed the S&P 500 benchmark in the early months of operation, with performance data that suggests consistent outperformance rather than a one‑off market timing event. The funds’ alignment with NAV, the dual strategy design, and the company’s public statements all point to a significant experiment in autonomous portfolio construction.
The next steps for the funds will likely include continued monitoring of performance, disclosure of risk metrics, and potential expansion of the AI framework to other asset classes or markets.
