-
1 Comment
Zhejiang Supor Co., Ltd is currently in a long term downtrend where the price is trading 14.7% below its 200 day moving average.
From a valuation standpoint, the stock is 35.9% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 3.3.
Zhejiang Supor Co., Ltd's total revenue rose by 6.8% to $5B since the same quarter in the previous year.
Its net income has increased by 14.0% to $765M since the same quarter in the previous year.
Finally, its free cash flow grew by 5.1% to $1B since the same quarter in the previous year.
Based on the above factors, Zhejiang Supor Co., Ltd gets an overall score of 4/5.
| Exchange | SHE |
|---|---|
| CurrencyCode | CNY |
| ISIN | CNE000001KS5 |
| Industry | Furnishings, Fixtures & Appliances |
| Sector | Consumer Cyclical |
| Dividend Yield | 5.6% |
|---|---|
| PE Ratio | 17.74 |
| Target Price | 53.324 |
| Market Cap | 37B |
| Beta | 0.34 |
Zhejiang Supor Co., Ltd. engages in the manufacture and sale of kitchen cookware and small appliances in China and internationally.The company offers aluminum and stainless steel cookware, wok, roaster, and pressure cooker; and electric pressure cooker, rice cooker, air fryer, electric kettle, high speed blender, breakfast combo, and home environmental appliances. Its cookware and electrical products are primarily exported to Japan, Europe, the United States, and Southeast Asia. The company was founded in 1994 and is headquartered in Hangzhou, China. Zhejiang Supor Co., Ltd. operates as a subsidiary of SEB SA.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002032.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