Brad Gerstner and Cathie Wood Like Snowflake (SNOW) and Robinhood (HOOD)
Investment heavyweights Brad Gerstner and Cathie Wood have recently aligned their portfolios with Snowflake (SNOW) and Robinhood (HOOD). Gerstner's Altimeter Capital, known for AI tech investments, holds a significant 1.9 million shares of Snowflake, accounting for 4.99% of his portfolio. Wood, recognized for aggressive growth in various sectors, opened a position in Snowflake with 269,539 shares.
In contrast, their approach to Robinhood was divergent, with Gerstner maintaining a steady 899,691 share position (0.92% of his portfolio) and Wood reducing hers by 13%, leaving roughly 5.24 million shares (3.41% of her portfolio).
Snowflake Inc. (NYSE:SNOW) provides a cloud data platform that assists businesses in managing their data, a necessity for AI technologies. The company's revenue surged by 33% year-over-year in Q1 2027, exceeding market expectations. Product revenue increased by 34%, significantly higher than previous quarters. Net revenue retention reached 126%, surpassing expectations.
Management has raised fiscal 2027 product revenue guidance to 31%, up from the previous 27% projection. Snowflake's AI tool, Snowflake Intelligence, allows non-technical employees to ask questions in plain English and receive answers from company data, having been adopted by over 2,500 accounts by fiscal Q4 2026.
Despite the stock's high valuation, with a forward non-GAAP P/E of 167.82 (625% above the sector median) and forward EV/sales of 18.25 (18.25 times sales, compared to a sector median of 3.58), Snowflake's unique position in the AI wave and its AI tool, Snowflake Intelligence, have made it an attractive investment for some. However, the premium paid for Snowflake's growth is a concern for skeptics, who argue that the price already assumes positive outcomes.
While acknowledging these risks, the analysis concludes that some AI stocks offer greater potential for higher returns within a shorter timeframe.
Written by urgent.news from Yahoo Finance's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.