-
1 Comment
Hunan Nanling Industrial Explosive Materials Co., Ltd is currently in a long term downtrend where the price is trading 14.2% below its 200 day moving average.
From a valuation standpoint, the stock is 57.7% cheaper than other stocks from the Basic Materials sector with a price to sales ratio of 1.7.
Hunan Nanling Industrial Explosive Materials Co., Ltd's total revenue sank by 30.3% to $537M since the same quarter in the previous year.
Its net income has increased by 2.9% to $15M since the same quarter in the previous year.
Finally, its free cash flow grew by 21.7% to $92M since the same quarter in the previous year.
Based on the above factors, Hunan Nanling Industrial Explosive Materials Co., Ltd gets an overall score of 3/5.
| ISIN | CNE000001PV8 |
|---|---|
| Exchange | SHE |
| Industry | Specialty Chemicals |
| CurrencyCode | CNY |
| Sector | Basic Materials |
| Market Cap | 15B |
|---|---|
| Beta | 0.58 |
| Target Price | 18 |
| Dividend Yield | 2.1% |
| PE Ratio | 18.34 |
Explosive Co., Ltd., together with its subsidiaries, engages in the research, development, production, and sale of civil blasting materials in China. It provides energy integration solutions; general contractor; infrastructure investor; ecosystem restoration solutions; and building materials, industrial products, and equipment, as well as acts as an urban development operator. The company was formerly known as Hunan Nanling Industrial Explosive Materials Co., Ltd. and changed its name to Explosive Co., Ltd. in May 2023. Explosive Co., Ltd. was founded in 2001 and is headquartered in Changsha, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002096.SHE 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 2026