$1.310
-0.020 (-1.50%)At close
Price Predictions
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BATL Prediction & Forecast by Similar Chart Analysis
Alphio's BATL stock price prediction model matches the current Battalion Oil Corp tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $1.32 (+0.99%). The 1-week path is $1.32 (+0.74%). Longer windows use the same pattern set plus seasonality; the 1-month and multi-year forecasts sit behind unlock because they include precise min / avg / max bands.
Should I Buy Battalion Oil Corp Stock?
Battalion Oil Corp (BATL) is a good buy right now due to its recent positive earnings report and the bullish sentiment in the energy sector driven by rising oil prices. The stock closed at 1.31, with a significant increase of over 11% following the surge in oil prices, which have risen over 42% in the past 20 days. Additionally, the forward P/E ratio is a low 1.96, suggesting the stock is undervalued compared to its earnings potential. However, the main risk is the recent negative net income of -64,808,000 in Q1 2026, which indicates ongoing financial challenges that investors should monitor closely.
BATL stock price ended at $1.31 on Friday, after losing -1.50%
Battalion Oil Corp (BATL) last closed at $1.31, losing -1.50%. These facts feed the 1-day and 1-week BATL price prediction above.
Forecast Drivers
Battalion Oil Corp (BATL) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bearish
SMA 200
Bearish
Similar Chart Patterns
Stocks whose recent price path most closely matches BATL, ranked by similarity.
Seasonality analysis for BATL
Historically the probability of a positive August return for BATL is 31.75%. January offers the highest probability of a positive month at 52.46%, while September is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
This page is for research only and is not investment advice. Models can be wrong. Past performance does not guarantee future results.