-
1 Comment
Vertex Energy, Inc is currently in a long term uptrend where the price is trading 393.8% above its 200 day moving average.
From a valuation standpoint, the stock is 93.8% cheaper than other stocks from the Energy sector with a price to sales ratio of 0.5.
Vertex Energy, Inc's total revenue sank by 5.9% to $40M since the same quarter in the previous year.
Its net income has dropped by 586.8% to $-5M since the same quarter in the previous year.
Finally, its free cash flow fell by 178.5% to $-4M since the same quarter in the previous year.
Based on the above factors, Vertex Energy, Inc gets an overall score of 2/5.
Exchange | NASDAQ |
---|---|
CurrencyCode | USD |
ISIN | US92534K1079 |
Sector | Energy |
Industry | Oil & Gas Refining & Marketing |
Market Cap | 5M |
---|---|
PE Ratio | None |
Target Price | 1.15 |
Beta | 1.37 |
Dividend Yield | None |
Vertex Energy, Inc., an energy transition company, that focuses on the production and distribution of conventional and alternative fuels. The company engages in refining and distributing petroleum products comprising the mobile refinery and related operations. It sells ferrous and non-ferrous recyclable metal products, and markets Group III base oils and other petroleum-based products, as well as provides transportation and marine salvage services. Vertex Energy, Inc. was founded in 2001 and is headquartered in Houston, Texas. On September 24, 2024, Vertex Energy, Inc., along with its affiliates, filed a voluntary petition for reorganization under Chapter 11 in the U.S. Bankruptcy Court for the Southern District of Texas.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for VTNR using our backtest tool. PyInvesting provides the backtesting software for you to backtest your investment strategy. Our backtest software is written using Python code and allows you to backtest stock, backtest etf, backtest options, backtest crypto and backtest forex online. Our backtesting Python framework is highly robust and gives you a realistic simulation of how your strategy would have performed in the past using backtest data.
© PyInvesting 2025