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Takeaway: Despite a recent 7.01% price rise, technical indicators remain bearish, and analyst expectations are out of sync with momentum. Investors should tread carefully.
Recent headlines paint a mixed picture for the semiconductor sector and Qualcomm's broader industry context:
Qualcomm has attracted a mix of analyst ratings in the past 20 days. The simple average rating is 4.00, while the performance-weighted rating is 1.88, indicating a generally negative sentiment from historical performance. Analysts show divergent views, with some labeling them as "good" (Rosenblatt’s Kevin Cassidy, 66.7% historical win rate) and others as "poor" (UBS’s Timothy Arcuri, 0.0% win rate).
There is a clear mismatch between analyst expectations and the stock’s recent 7.01% upward price movement. This suggests caution in relying solely on recent optimism.
Here's how Qualcomm’s key fundamental metrics are shaping up:
Big money is currently flowing out of Qualcomm, with the overall inflow ratio at just 38.26%. The breakdown by fund size reveals a uniformly negative trend:
This broad-based outflow is a red flag for investors. Internal diagnostic score: 6.92 (good).
The technical outlook for Qualcomm is underwhelming, with 3 bearish signals vs. only 1 bullish signal. The internal technical score is 2.57, reflecting a weak trend and high risk of further declines. Here are the key signals:
Recent bearish signals emerged from the following dates:
Technical indicators suggest the stock is in a weak state, with bearish signals dominating the chart. The consensus from technical analysis is that investors should avoid the stock due to a high risk of further decline.
Qualcomm finds itself in a challenging position: fundamentals and analyst ratings are mixed, technicals are bearish, and large money is withdrawing. While the company’s recent 7.01% price rise may appear encouraging, the internal diagnostic scores tell a different story. Consider waiting for a more favorable technical setup or stronger earnings guidance before committing capital.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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