Roma Green Finance Ltd（ROMA）价格预测

$6.000

-0.724 (-12.07%)收盘时

价格预测

1-Day Price Prediction

+1.81%

1-Week Prediction

+5.16%

1-Month Prediction

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2026 Prediction

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2030 Prediction

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在 App 中打开以解锁更长周期的预测。

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ROMA 相似图表分析预测

Alphio's ROMA stock price prediction model matches the current Roma Green Finance Ltd tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $6.11 (+1.81%). The 1-week path is $6.31 (+5.16%). 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.

该买入 Roma Green Finance Ltd 股票吗？

Roma Green Finance Ltd is not a good buy right now due to its current price of $6.00, a very low RSI of 14.207 indicating oversold conditions, and a staggering 25.19% decline over the last five days. The company has reported negative earnings per share for the upcoming quarters, with a forward P/E of 0, which raises concerns about its profitability. Additionally, the gross margin has dropped to 6.96% in the latest quarter, suggesting operational challenges. The main risk is the negative sentiment reflected in the recent 12.07% drop in stock price yesterday, indicating potential further declines.

ROMA 股价于 Friday 收于 $6.00，此前下跌 -12.07%

Roma Green Finance Ltd (ROMA) last closed at $6, losing -12.07%. These facts feed the 1-day and 1-week ROMA price prediction above.

预测驱动因素

Roma Green Finance Ltd（ROMA）的预测驱动因素综合了相似的图表形态、季节性与移动平均线。

Similar patterns

Positive

Bullish

Seasonality

Positive

Bullish

SMA 20

Negative

Bearish

SMA 200

Negative

Bearish

相似图表形态

近期走势与 ROMA 最接近的股票，按相似度排序。

SOC

89.00%

+41.56%

88.07%

-1.24%

CTVA

87.92%

+2.81%

LCID

87.54%

-6.86%

GPN

87.27%

-14.78%

ROMA 季节性分析

Historically the probability of a positive October return for ROMA is 63.49%. June offers the highest probability of a positive month at 68.33%, 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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