$10.280
+0.005 (+0.05%)At close
Price Predictions
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HAVA Prediction & Forecast by Similar Chart Analysis
Alphio's HAVA stock price prediction model matches the current Harvard Ave Acquisition Corp tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $10.32 (+0.39%). The 1-week path is $10.64 (+3.50%). 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 Harvard Ave Acquisition Corp Stock?
Currently, HAVA is not a strong buy. The stock is trading at $10.27, which is close to its 52-week high of $10.32, indicating limited upside potential. The RSI is at 51.39, suggesting the stock is neither overbought nor oversold. While the company has shown a positive trend in net income with a significant increase to $1,135,236 in Q1 2026, the forward P/E ratio is 0, indicating uncertainty in future earnings. The main risk is the high price-to-book ratio of 2279.89, which suggests that the stock may be overvalued relative to its book value.
HAVA stock price ended at $10.28 on Wednesday, after rising +0.05%
Harvard Ave Acquisition Corp (HAVA) last closed at $10.2799997, gaining +0.05%. These facts feed the 1-day and 1-week HAVA price prediction above.
Forecast Drivers
Harvard Ave Acquisition Corp (HAVA) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Similar patterns
Bullish
Seasonality
Bullish
SMA 20
Bullish
SMA 200
Bullish
Similar Chart Patterns
Stocks whose recent price path most closely matches HAVA, ranked by similarity.
Seasonality analysis for HAVA
Historically the probability of a positive November return for HAVA is 100.00%. February offers the highest probability of a positive month at 100.00%, while January is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
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This page is for research only and is not investment advice. Models can be wrong. Past performance does not guarantee future results.