$0.940
+0.039 (+4.16%)收盤時
價格預測
在 App 中開啟以解鎖更長週期的預測。
LDI 相似圖表分析預測
Alphio's LDI stock price prediction model matches the current loanDepot Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $0.96 (+2.45%). The 1-week path is $0.98 (+3.75%). 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.
該買進 loanDepot Inc 股票嗎?
LoanDepot Inc is not a good buy right now due to its current price of $0.9604, which is below the analyst price target of $1. Additionally, the company has a negative forward P/E of 14.86, indicating potential valuation concerns. The main risk is the high debt-to-equity ratio of 1373.39%, which suggests significant leverage and financial instability.
LDI 股價於 Thursday 收在 $0.94,此前上漲 +4.16%
loanDepot Inc (LDI) last closed at $0.9399, gaining +4.16%. These facts feed the 1-day and 1-week LDI price prediction above.
預測驅動因素
loanDepot Inc(LDI)的預測驅動因素綜合了相似的圖表形態、季節性與移動平均線。
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bullish
SMA 200
Bearish
相似圖表形態
近期走勢與 LDI 最接近的股票,依相似度排序。
LDI 季節性分析
Historically the probability of a positive September return for LDI is 47.73%. December offers the highest probability of a positive month at 51.16%, while March is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
LDI 十年價格預測
| 月份 | 最低價 | 平均價 | 最高價 | 潛在報酬率 |
|---|---|---|---|---|
| Sep 2026 | $1.37 | $1.61 | $1.70 | +71.82% |
| Oct 2026 | $1.20 | $1.27 | $1.46 | +35.52% |
| Nov 2026 | $1.41 | $1.61 | $1.89 | +71.67% |
| Dec 2026 | $1.10 | $1.26 | $1.26 | +33.64% |
2026 年,loanDepot Inc(LDI)預計區間為 $1.10 至 $1.89。
loanDepot Inc 2026 年月度預測
2026 年 Sep,loanDepot Inc 預計均價 $1.61,最低 $1.37,最高 $1.70。
2026 年 Oct,loanDepot Inc 預計均價 $1.27,最低 $1.20,最高 $1.46。
2026 年 Nov,loanDepot Inc 預計均價 $1.61,最低 $1.41,最高 $1.89。
2026 年 Dec,loanDepot Inc 預計均價 $1.26,最低 $1.10,最高 $1.26。
本頁僅供研究參考,不構成投資建議。模型可能出錯。過往表現不代表未來結果。