$2.780
+0.093 (+3.35%)At close
Price Predictions
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DSX Prediction & Forecast by Similar Chart Analysis
Alphio's DSX stock price prediction model matches the current Diana Shipping Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $2.80 (+0.88%). The 1-week path is $2.78 (+0.15%). 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 Diana Shipping Inc Stock?
Diana Shipping Inc is a good buy right now, trading at a current price of 2.78, which is supported by a strong year-to-date change of +65.48% and a solid forward P/E of 3.19. The company recently extended a charter with Cargill, increasing the gross charter rate significantly, which is expected to enhance revenue. However, the RSI is at 74.14, indicating that the stock may be overbought, which is a risk to consider.
DSX stock price ended at $2.78 on Friday, after rising +3.35%
Diana Shipping Inc (DSX) last closed at $2.78, gaining +3.35%. These facts feed the 1-day and 1-week DSX price prediction above.
Analyst Consensus
Diana Shipping Inc (DSX): 3 buy, 8 hold, 2 sell. Outlook: Hold.
Sell / Buy
Technical signals summary based on buy and sell indicators. The gauge shows the overall market view.
Forecast Drivers
Diana Shipping Inc (DSX) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bullish
SMA 200
Bullish
Similar Chart Patterns
Stocks whose recent price path most closely matches DSX, ranked by similarity.
Seasonality analysis for DSX
Historically the probability of a positive August return for DSX is 31.75%. March offers the highest probability of a positive month at 66.67%, while October 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.