$24.391
+0.144 (+0.59%)At close
Price Predictions
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BRKL stock price ended at $24.39 on Friday, after rising +0.59%
Brookline Bancorp Inc (BRKL) last closed at $24.3907, gaining +0.59%. These facts feed the 1-day and 1-week BRKL price prediction above.
Analyst Consensus
Brookline Bancorp Inc (BRKL): 2 buy, 3 hold, 0 sell. Outlook: Hold.
Sell / Buy
Technical signals summary based on buy and sell indicators. The gauge shows the overall market view.
Forecast Drivers
Brookline Bancorp Inc (BRKL) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Seasonality
Bearish
SMA 20
Bullish
SMA 200
Bullish
Seasonality analysis for BRKL
Historically the probability of a positive August return for BRKL is 12.70%. November offers the highest probability of a positive month at 100.00%, while April is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
10-year price projections for BRKL
| Month | Min Price | Avg Price | Max Price | Potential ROI |
|---|---|---|---|---|
| Aug 2026 | $11.38 | $14.37 | $15.22 | -41.10% |
| Sep 2026 | $5.83 | $10.82 | $10.95 | -55.64% |
| Oct 2026 | $14.39 | $14.88 | $19.81 | -38.99% |
| Nov 2026 | $8.70 | $11.67 | $16.00 | -52.14% |
| Dec 2026 | $13.74 | $16.04 | $18.71 | -34.23% |
In 2026, Brookline Bancorp Inc (BRKL) is projected to range from $5.83 to $19.81.
Brookline Bancorp Inc 2026 monthly forecast
In Aug 2026, Brookline Bancorp Inc is projected to average $14.37, with a low of $11.38 and high of $15.22.
In Sep 2026, Brookline Bancorp Inc is projected to average $10.82, with a low of $5.83 and high of $10.95.
In Oct 2026, Brookline Bancorp Inc is projected to average $14.88, with a low of $14.39 and high of $19.81.
In Nov 2026, Brookline Bancorp Inc is projected to average $11.67, with a low of $8.70 and high of $16.00.
In Dec 2026, Brookline Bancorp Inc is projected to average $16.04, with a low of $13.74 and high of $18.71.
This page is for research only and is not investment advice. Models can be wrong. Past performance does not guarantee future results.