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Old Dominion Freight (ODFL) is currently trading in a downward trend, with a recent price drop of 3.17%. This comes amid 4 bearish indicators on the technical side and a low technical score of 2.23 (internal diagnostic score, 0-10), signaling caution for investors. Analysts remain mixed but broadly neutral, with a simple average rating of 3.56 and a weighted performance-based rating of 3.26.
The consensus among analysts is relatively neutral, with 4 out of 8 recent ratings labeled "Neutral," and only one "Sell" rating. The average analyst rating is 3.56, with a performance-weighted score of 3.26, reflecting caution and lower-than-expected confidence in the stock's near-term potential.
However, the falling price trend of ODFL is at odds with this mild optimism. Key fundamentals include:
Overall, the fundamental score is 3.71 (internal diagnostic score), suggesting a moderately stable company but one lacking strong growth momentum.
Despite the recent price drop, money flow for ODFL is positive, with an overall inflow ratio of 51.62% and all major investor categories showing inflows. The largest inflow is observed among extra-large investors (inflow ratio 52.70%), suggesting big money is cautiously entering the stock despite its bearish technical indicators.
The technical outlook for ODFL is clearly weak, with 4 bearish indicators and 0 bullish ones in the last 5 days. Here are the most notable signals:
Recent chart patterns include:
Overall, the technical score is 2.23 (internal diagnostic score), with the model advising to avoid the stock due to its weak momentum and 4 out of 4 negative indicators.
Old Dominion Freight is facing a challenging environment with mixed analyst signals, weak technicals, and moderate fundamentals. While big money is entering the stock, the technical indicators are heavily bearish. Given this backdrop, we recommend investors to consider waiting for a clearer reversal signal or a pullback to safer levels. In the meantime, keep a close eye on upcoming analyst revisions and macroeconomic factors that could impact logistics demand.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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