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Takeaway: Despite a modest 2.85% price rise recently, the technical and momentum outlook for
(OMC) is weak, with bearish signals dominating and a strong suggestion to avoid the stock at this time.Analysts remain divided on Omnicom Group, with a simple average rating of 3.50 and a historically weighted average of 2.64. This indicates mixed expectations, with no strong consensus. The ratings include a “Buy” and a “Neutral” from the past two active analysts: David Karnovsky (JP Morgan) and Steven Lee Cahall (Wells Fargo). Their historical win rates are 40% and 50% respectively, suggesting a cautious approach is warranted.
Fundamental Highlights:
These values reflect a mix of strengths and challenges. While profitability and efficiency are somewhat robust, valuation metrics are stretched, contributing to the overall caution.
Big-money flows are negative, with large, extra-large, and medium investors showing outflows. Retail flows, however, are more positive, indicating some retail participation despite institutional caution.
With a fund-flow score of 7.18, the stock is currently rated as “good,” but the divergence between retail and institutional sentiment suggests a need for caution.
Technically, the outlook is weak, with 2 bearish indicators and 0 bullish in the recent five-day window. The internal diagnostic score for technical conditions is 1.58, suggesting it's best to avoid at this time.
Key Indicators & Scores:
Recent Chart Patterns:
With such persistent overbought indicators and bearish momentum, the risk of a downward correction is elevated.
Omnicom Group (OMC) appears to be at a crossroads. While some fundamentals and retail flows hint at potential, the technical setup and analyst dispersion suggest caution. The internal diagnostic technical score of 1.58 and bearish indicators signal a weak trend. Investors are advised to consider waiting for a pull-back or clearer momentum 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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