-
1 Comment
Denox Environmental & Technology Holdings Limited is currently in a long term uptrend where the price is trading 47.4% above its 200 day moving average.
From a valuation standpoint, the stock is 50.9% cheaper than other stocks from the Industrials sector with a price to sales ratio of 1.1.
Denox Environmental & Technology Holdings Limited's total revenue sank by 51.0% to $22M since the same quarter in the previous year.
Its net income has increased by 79.3% to $-5M since the same quarter in the previous year.
Finally, its free cash flow grew by 43.3% to $-3M since the same quarter in the previous year.
Based on the above factors, Denox Environmental & Technology Holdings Limited gets an overall score of 4/5.
| CurrencyCode | HKD |
|---|---|
| ISIN | KYG2810N1088 |
| Sector | Industrials |
| Exchange | HK |
| Industry | Pollution & Treatment Controls |
| PE Ratio | None |
|---|---|
| Market Cap | 43M |
| Target Price | None |
| Beta | 0.99 |
| Dividend Yield | None |
Denox Environmental & Technology Holdings Limited, an investment holding company, designs, develops, manufactures, and sells DeNOx catalysts in the People's Republic of China and internationally. It offers plate-type DeNOx catalysts, honey-comb DeNOx catalysts, and DeNOx catalysts for vehicles. The company sells its plate-type DeNOx catalysts to coal-fired power plants; engineering, procurement, and construction services providers; and boiler manufacturers. It also develops catalysts for diesel-powered vehicles and natural gas-powered vehicles. The company was founded in 2010 and is headquartered in Beijing, the People's Republic of China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 1452.HK 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
