iShares Core Growth Allocation ETF vs Innodata Inc — how do they compare? iShares Core Growth Allocation ETF trades at $69.87, while Innodata Inc trades at $62.95 (market cap $2.05B). The key difference: iShares Core Growth Allocation ETF is trading nearer its 52-week high, Innodata Inc nearer its low. Which is the better fit depends on your goals.
| AOR | INOD | |
|---|---|---|
52-Week High | $70.12 | $121.50 |
52-Week Low | $62.26 | $34.45 |
Market Cap | — | $2.05B |
Sector | — | Technology |
Enterprise Value | — | $1.80B |
Signals from Pluang's Aura AI — not financial advice
No Aura AI signal available yet.
INOD trades at $62.33, down 4.81% over 24 hours, with a bearish technical signal from moving averages despite neutral oscillators. The company reported strong Q2 2026 earnings, beating estimates with EPS of $0.41 versus $0.21 expected, driven by 58% revenue growth and AI demand expansion. Valuation ratios remain elevated, with a P/E of 48.24 and P/S of 6.79, reflecting high growth expectations. Recent news highlights AI-driven growth and leadership transition plans.
Outlook is positive due to robust AI momentum and earnings beats, but risks include premium valuation and customer concentration. Analyst consensus is bullish with a $130 price target, suggesting significant upside from current levels. Investors should weigh growth potential against execution risks in a competitive AI services market.
Trailing returns across standard periods
The fund is a fund of funds and seeks its investment objective by investing primarily in underlying funds that themselves seek investment results corresponding to their own respective underlying indexes. It generally will invest at least 80% of its assets in the component securities of its underlying index. The index measures the performance of the S&P Dow Jones Indices LLC proprietary allocation model.
Read more on AOR →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 →