AlphaVest Acquisition Corp

Análisis de la acción AlphaVest Acquisition Corp (ATMV)

$10.300

+3.224 (+31.30%)Al cierre

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High
15.000
Open
10.410
VWAP
11.48
Vol
12.64M
Mkt Cap
Low
9.140
Amount
145.12M
EV/EBITDA, TTM
0.00

AlphaVest Acquisition Corp. is a blank check company. The Company is formed for the purpose of effecting a merger, stock exchange, asset acquisition, stock purchase, reorganization, or similar business combination with one or more businesses. The Company intends to focus its search on businesses throughout Asia. The Company has not generated any revenue.

Métricas de valoración

The current forward P/E ratio for AlphaVest Acquisition Corp (ATMV) is 0.00, compared to its 5-year average forward P/E of 0.00.

Forward P/E

Strongly Undervalued
5Y Average P/E
0.00
Current P/E
0.00
Sobrevalorada
0.00
Infravalorada
0.00

Forward EV/EBITDA

Strongly Undervalued
5Y Average EV/EBITDA
0.00
Current EV/EBITDA
0.00
Sobrevalorada
0.00
Infravalorada
0.00

Forward P/S

Strongly Undervalued
5Y Average P/S
0.00
Current P/S
0.00
Sobrevalorada
0.00
Infravalorada
0.00

Alphio AI Price Scenarios for ATMV

Scenario prices are the last monthly forecast band of the current year. Probabilities are fixed model weights (25 / 50 / 25), not guarantees.

B

Bull

Bull · 25%ATMV

$13.14

Precio del escenario

B

Base

Base · 50%ATMV

$11.76

Precio del escenario

B

Bear

Bear · 25%ATMV

$9.61

Precio del escenario

Whales holding ATMV

C

Cerberus Capital Management, L.P.

+ HoldingATMV

-22.94%

3M Return

ATMV FAQ — answered by Alphio AI

AlphaVest Acquisition Corp. is a blank check company. The Company is formed for the purpose of effecting a merger, stock exchange, asset acquisition, stock purchase, reorganization, or similar business combination with one or more businesses. The Company intends to focus its search on businesses throughout Asia. The Company has not generated any revenue. It operates in the Financials sector (BLANK CHECKS industry).

Esta página es solo para investigación y no constituye asesoramiento de inversión. Los modelos pueden equivocarse. El rendimiento pasado no garantiza resultados futuros.

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