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Tyson Foods (TSN) is showing a sharp bearish bias across technical indicators, with no bullish signals in the last 5 days and 5 out of 5 signals leaning negative — an internal diagnostic score of just 1.03.
Analyst sentiment is neutral, with one analyst from J.P. Morgan rating
as "Neutral" recently. The simple average rating is 3.00, while the performance-weighted rating is 3.03, showing strong consistency. However, this neutral outlook contrasts with the stock’s 1.27% price rise in recent days, which suggests analysts may be underestimating short-term momentum — or the market is pricing in factors they haven’t yet modeled.Key fundamental factor values include:
These metrics suggest modest efficiency in asset utilization and debt management, but none stand out as strong positives. Revenue-MV and Cash-MV scores are relatively high (3.00 each), but these are more about market capitalization positioning than intrinsic strength.
Big-money investors are pulling back slightly with the block trend negative (−49.90% inflow), while small and medium retail investors are still pushing in, with inflow ratios above 50% for small (52.11%) and medium-sized traders (50.72%). This discrepancy suggests that institutional traders are cautious, while retail enthusiasm remains in play. The fund flow score is 7.89 (internal diagnostic score), indicating good net flow but not a strong bull signal.
Tyson Foods is facing a mountain of bearish signals in the last 5 days, including:
On the calendar:
These signals suggest a very weak momentum environment, with more risk of downward correction than upside.
Tyson Foods faces a challenging near-term outlook with five bearish signals, no bullish ones, and a technical score of 1.03. While fundamentals are mixed — with some modestly positive ratios — the stock is showing no strong upside catalysts. Institutional money is pulling back and the technical environment is highly bearish.
Actionable takeaway: Consider waiting for a pull-back or clearer bullish signals before entering long positions. For now, the risk-reward is skewed toward the downside.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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