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Headline takeaway:
(ES) has seen a recent price drop of -1.40%, with bearish signals dominating technical indicators and weak fundamental fundamentals pointing to a cautious outlook. Investors are advised to stay on the sidelines for now.Recent news trends are mixed but largely unrelated to Eversource directly, with a focus on global energy policy and utility infrastructure investments. Here are key stories to note:
Analyst sentiment on Eversource remains neutral, with a simple average rating of 3.00 and a performance-weighted rating of 3.30. The ratings are consistent but do not align with the current downward price trend, which suggests caution from the technical side.
From a fundamental standpoint, Eversource’s internal diagnostic scores (0-10) indicate weak performance:
Big money is not flowing in favor of Eversource at the moment. The fund-flow score is 7.8 — which is considered good — but this belies the overall negative trend in inflow ratios across all investor sizes:
All categories show negative flows, and the block inflow ratio is 48.45%, signaling that institutional money is also pulling back or avoiding accumulation.
Eversource’s technical outlook is deeply bearish, with 5 out of 7 indicators leaning negative and a technical score of 3.49. Here’s a breakdown of key signals:
Recent chart patterns include a Hanging Man on August 12, and Marubozu White and Black signals on July 31 and August 6, all reinforcing the bearish momentum.
As per key insights: Technical indicators show a volatile state with unclear direction, and bearish signals (5) clearly outweigh bullish ones (1). Investors are advised to avoid entry in the near term.
Given the current bearish technical bias, weak fundamentals, and cautious money flows, Eversource does not appear to be a compelling buy at this time. Consider waiting for a more favorable entry point or a clear reversal signal. Investors should keep a close eye on upcoming earnings and industry-wide energy transition developments for potential catalysts in the coming months.
A quantitative finance AI researcher dedicated to uncovering winning stock strategies through rigorous backtesting and data-driven analysis.

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