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Compare ARK Autonomous Technology & Robotics ETF (ARKQ) vs Innodata Inc (INOD) Price & Performance

ARK Autonomous Technology & Robotics ETFTrade
Innodata IncTrade

Price performance (Past 24H)

Key statistics

ARK Autonomous Technology & Robotics ETF vs Innodata Inc — how do they compare? ARK Autonomous Technology & Robotics ETF trades at $129.02, while Innodata Inc trades at $62.25 (market cap $2.05B). The key difference: ARK Autonomous Technology & Robotics ETF is trading nearer its 52-week high, Innodata Inc nearer its low. Which is the better fit depends on your goals.

ARKQINOD
Sector
Sector/ThematicTechnology
52-Week High
$143.82$121.50
52-Week Low
$95.28$34.45
Market Cap
$2.05B
Enterprise Value
$1.80B

Aura AI Summary

Signals from Pluang's Aura AI — not financial advice

ARK Autonomous Technology & Robotics ETF

No Aura AI signal available yet.

Innodata Inc

INOD trades at $61.40, down 1.33% today, but maintains a bullish technical signal with oscillators supporting upside momentum. The company reported strong Q2 2026 results, beating EPS estimates with $0.41 versus $0.21 expected, driven by 58% revenue growth and AI-driven demand expansion. Valuation ratios remain elevated with a P/E of 48.62, reflecting high growth expectations.

Outlook is positive given consistent earnings beats and AI sector tailwinds, but risks include premium valuation sensitivity and customer concentration. Analyst consensus is bullish with a $130 price target, suggesting significant upside potential if execution continues.

Returns comparison

Trailing returns across standard periods

About ARK Autonomous Technology & Robotics ETF

ARKQ is an actively managed ETF that invests in autonomous technology and robotics. It focuses on disruptive innovations like autonomous mobility, electric vehicles, 3D printing, and energy storage, with holdings such as Tesla and Teradyne.

Read more on ARKQ

About Innodata Inc

Innodata is a global data engineering company that provides solutions for training AI models. It helps enterprises solve complex data challenges through high-quality data annotation and digital transformation.

Read more on INOD