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Headline Takeaway:
(SES.N) is under pressure with a recent price drop of -8.67%, and our internal diagnostic score (0-10) for fundamentals stands at 1.27 — suggesting caution for potential buyers.Recent headlines offer a mixed landscape for AI and tech sectors. Notable stories include:
Despite the recent price drop, a Cantor Fitzgerald analyst, Derek Soderberg, has issued a "Buy" rating with a historical win rate of 66.7%. However, the simple average rating is 4.00 and the performance-weighted average is 3.70 — indicating a mixed consensus. These scores are disconnected from the current negative price trend (-8.67%), suggesting that expectations don’t fully align with recent market behavior.

Key fundamentals (using our proprietary model scores) show:
The picture is bleak: most financial metrics are negative, with internal diagnostic scores reflecting poor alignment with positive investment outcomes.
Money is moving out of SES AI despite retail optimism. The fund-flow score is a 7.64 (good), driven by retail inflows (51.6% of total inflows), while institutional investors are net outflows. Specifically:
This pattern suggests retail optimism isn’t yet convincing big money — a warning sign for speculative plays.
SES AI's technicals are underperforming. The internal technical score is 3.31, and the chart has shown more bearish than bullish signals:
Recent chart patterns (last 5 days) include:
The key technical insight is that bearish indicators (5) far outweigh bullish ones (1). The trend is weak, and the volatility without clear direction makes it a high-risk scenario.
SES AI remains a volatile and bearish play, with weak fundamentals, mixed analyst sentiment, and a technical profile that suggests caution. While a rare bullish pattern (Inverted Hammer) appeared recently, the broader trend is negative. Given the internal diagnostic scores and the bearish fund flows, investors are advised to avoid this stock for now. Consider watching upcoming earnings or capital-raising developments for a potential turnaround signal.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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