-
1 Comment
Jinhe Biotechnology CO., LTD is currently in a long term uptrend where the price is trading 9.0% above its 200 day moving average.
From a valuation standpoint, the stock is 78.2% cheaper than other stocks from the Healthcare sector with a price to sales ratio of 2.1.
Jinhe Biotechnology CO., LTD's total revenue rose by 13.8% to $608M since the same quarter in the previous year.
Its net income has dropped by 63.1% to $15M since the same quarter in the previous year.
Finally, its free cash flow grew by 1203.4% to $23M since the same quarter in the previous year.
Based on the above factors, Jinhe Biotechnology CO., LTD gets an overall score of 4/5.
| Sector | Healthcare |
|---|---|
| Industry | Drug Manufacturers - Specialty & Generic |
| Exchange | SHE |
| CurrencyCode | CNY |
| ISIN | CNE100001HK7 |
| Beta | 0.54 |
|---|---|
| Market Cap | 5B |
| PE Ratio | 50.38 |
| Target Price | None |
| Dividend Yield | 1.5% |
Jinhe Biotechnology CO., LTD. produces and sells veterinary medicines in China. The company offers chlortetracycline feed grade, an antimicrobial drug for the inhibition and treatment of white dysentery, enteritis, pneumonia, typhoid, paratyphoid, cholera, etc. in poultry and livestock; and chlortetracycline hydrochloride for the inhibition and treatment of pullorum disease, typhoid, and swine enteritis, as well as bacterial diseases, including paratyphoid and cholera. It also exports its products to the United States, South-east Asia, Latin America, Europe, etc. Jinhe Biotechnology CO., LTD. was founded in 1990 and is based in Dalian, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002688.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 2025
