As the AI investment boom enters a new phase, a bold wave of financial innovation is giving high-risk, high-reward investors even more powerful tools. Tradr ETFs, a rising name in the leveraged fund space, has officially launched options trading on five 2× leveraged ETFs, all focused on AI infrastructure and advanced computing, drawing more than $60 million in assets in just eight trading days.
With AI continuing to reshape industries—from semiconductors to nuclear-powered data centers—this move comes at a moment when investors are looking for precision instruments to ride the AI megatrend without waiting years for returns.
Risk Meets Reward: Why This Launch Matters for Investors
The five leveraged ETFs—tickered CWVX, SMU, ASTX, GEVX, and CEGX—track a curated group of companies at the forefront of AI compute and infrastructure, including names like CoreWeave, NuScale Power, and Gevo. The 2× exposure means these ETFs are designed to deliver double the daily return (or loss) of their respective indices or thematic baskets.
Tradr’s offering stands out in a crowded ETF landscape because it hits three sweet spots simultaneously:
- AI infrastructure: A niche that’s gained immense traction with Nvidia’s rise and hyperscaler capex surges.
- Leveraged exposure: Enabling faster gains—or steeper losses—for active traders.
- Options trading access: Offering further flexibility and hedging strategies for tactical positioning.
According to PR Newswire (July 24, 2025), “Investor demand has exceeded early expectations, especially in CWVX, which saw the fastest asset accumulation among new thematic ETFs this quarter.”
Decoding the Strategy Behind These AI-Leveraged ETFs
Each fund tracks a highly focused thematic basket aligned with AI tailwinds:
- CWVX: Anchored in advanced data center operators and cloud infrastructure plays.
- SMU: A mix of AI-enabling small modular nuclear reactors (NuScale) and grid tech.
- ASTX & GEVX: Focused on AI-adjacent sustainability and clean fuel firms.
- CEGX: AI components in robotics and next-gen semiconductors.
These aren’t your average passive ETFs. They are actively managed and rebalanced daily to maintain 2× leverage, making them more suitable for short-term tactical moves rather than long-term holds. As such, they cater more to sophisticated investors looking to amplify directional bets during market swings.
The Bigger Picture: AI Infrastructure Is the New Oil
The timing of this launch is no accident. AI infrastructure is exploding—Alphabet just raised its 2025 capex guidance to $85 billion, largely to scale up data center and GPU capacity. Meanwhile, Microsoft and Amazon are racing to secure power contracts for AI training workloads, driving renewed interest in AI-powered nuclear tech.
Analysts at J.P. Morgan have noted that “AI compute buildouts are now one of the fastest-growing capex lines across the S&P 500—on par with 5G during its peak.”
Tradr’s leveraged ETFs are designed to ride these ripples—giving investors a focused lens on the physical backbone of AI, beyond the usual chipmakers and SaaS giants.
Key Investment Insight: Play with Precision, Not Emotion
For retail and institutional investors alike, the emergence of leveraged AI ETFs with options access opens doors—but not without a warning sign. These products magnify both gains and losses, and are not designed for buy-and-hold portfolios.
Instead, investors might:
- Use options strategies (e.g., spreads or protective puts) to express conviction or manage downside risk.
- Monitor intraday momentum and sector rotations for short-term entries/exits.
- Pair exposure with non-leveraged AI funds to smooth volatility across positions.
As Bloomberg ETF strategist Eric Balchunas puts it: “Leveraged thematic ETFs are like racecars—they’re powerful but unforgiving. Use them with a seatbelt, helmet, and a plan.”
Stay Ahead of the Curve
As AI continues to dominate market narratives and investor portfolios, products like Tradr’s new leveraged ETFs will play an increasingly visible role—especially for traders hunting for high-octane exposure to the AI arms race.
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