-
1 Comment
Enviva Partners, LP is currently in a long term uptrend where the price is trading 11.5% above its 200 day moving average.
From a valuation standpoint, the stock is 79.7% cheaper than other stocks from the Basic Materials sector with a price to sales ratio of 2.0.
Enviva Partners, LP's total revenue rose by 38.3% to $277M since the same quarter in the previous year.
Its net income has dropped by 146.8% to $-435K since the same quarter in the previous year.
Finally, its free cash flow grew by 290.3% to $37M since the same quarter in the previous year.
Based on the above factors, Enviva Partners, LP gets an overall score of 4/5.
Sector | Basic Materials |
---|---|
Industry | Lumber & Wood Production |
Exchange | NYSE |
CurrencyCode | USD |
ISIN | US29414J1079 |
Market Cap | 31M |
---|---|
PE Ratio | None |
Target Price | 4 |
Beta | 0.84 |
Dividend Yield | None |
Enviva Inc. produces, processes, supplies, and sells utility-grade wood pellets. The company's products are used as a fuel for coal in dedicated biomass or co-fired coal power plants. It also owns and operates wood pellet production plants. The company serves power generators in the United Kingdom, the European Union, and Japan The company was formerly known as Enviva Partners, LP and changed its name to Enviva Inc. in December 2021. Enviva Inc. was incorporated in 2013 and is headquartered in Bethesda, Maryland. On March 12, 2024, Enviva Inc., along with its affiliates, filed a voluntary petition for reorganization under Chapter 11 in the U.S. Bankruptcy Court for the Eastern District of Virginia.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for EVA 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