$71.690
-1.376 (-1.92%)At close
Price Predictions
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LOAR Prediction & Forecast by Similar Chart Analysis
Alphio's LOAR stock price prediction model matches the current Loar Holdings Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $73.20 (+2.10%). The 1-week path is $72.64 (+1.33%). 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 Loar Holdings Inc Stock?
Loar Holdings Inc is currently priced at $71.69, with a forward P/E ratio of 61.73, indicating high expectations for future earnings growth. The recent RSI of 32.27 suggests the stock is oversold, which could indicate a potential buying opportunity. However, the stock has seen a 4.41% decline over the past five days, and hedge funds have increased selling by 432.77%, indicating caution in the market. Therefore, while there are positive catalysts such as raised earnings guidance and strong revenue growth, the significant insider selling and high valuation metrics suggest a hold position for now.
LOAR stock price ended at $71.69 on Friday, after losing -1.92%
Loar Holdings Inc (LOAR) last closed at $71.69, losing -1.92%. These facts feed the 1-day and 1-week LOAR price prediction above.
Forecast Drivers
Loar Holdings Inc (LOAR) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Similar patterns
Bullish
Seasonality
Bullish
SMA 20
Bearish
SMA 200
Bullish
Similar Chart Patterns
Stocks whose recent price path most closely matches LOAR, ranked by similarity.
Seasonality analysis for LOAR
Historically the probability of a positive August return for LOAR is 66.67%. October offers the highest probability of a positive month at 100.00%, while March 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.