-
1 Comment
Shanghai Anoky Group Co., Ltd is currently in a long term downtrend where the price is trading 3.8% below its 200 day moving average.
From a valuation standpoint, the stock is 2.1% more expensive than other stocks from the Basic Materials sector with a price to sales ratio of 4.1.
Shanghai Anoky Group Co., Ltd's total revenue sank by 4.5% to $256M since the same quarter in the previous year.
Its net income has increased by 2.1% to $35M since the same quarter in the previous year.
Finally, its free cash flow fell by 1723.2% to $-65M since the same quarter in the previous year.
Based on the above factors, Shanghai Anoky Group Co., Ltd gets an overall score of 1/5.
Exchange | SHE |
---|---|
CurrencyCode | CNY |
ISIN | CNE100000ND2 |
Sector | Basic Materials |
Industry | Specialty Chemicals |
Market Cap | 6B |
---|---|
PE Ratio | None |
Target Price | 13.33 |
Beta | 0.77 |
Dividend Yield | 0.7% |
Shanghai Anoky Group Co., Ltd provides dyeing and finishing solutions for textile fabrics and special needs in China and internationally. It produces and sells disperse dyes under the ANOCRON brand, reactive dyes under the ANOZOL brand, wool reactive dyes under the ANOFIX brand, acid dyes under the ANOSET brand, finishing auxiliaries under the ANOKE brand, and polyamide dyes under the ANOMEN brand. The company was formerly known as Shanghai ANOKY Textile Chem Co., Ltd. and changed its name to Shanghai Anoky Group Co., Ltd in October 2014. Shanghai Anoky Group Co., Ltd was founded in 1999 and is based in Shanghai, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 300067.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