-
1 Comment
Changshu Tianyin Electromechanical Co.,Ltd is currently in a long term uptrend where the price is trading 6.8% above its 200 day moving average.
From a valuation standpoint, the stock is 10.6% more expensive than other stocks from the Industrials sector with a price to sales ratio of 5.6.
Changshu Tianyin Electromechanical Co.,Ltd's total revenue rose by 4.2% to $217M since the same quarter in the previous year.
Its net income has increased by 4.1% to $31M since the same quarter in the previous year.
Finally, its free cash flow grew by 80.5% to $-8M since the same quarter in the previous year.
Based on the above factors, Changshu Tianyin Electromechanical Co.,Ltd gets an overall score of 4/5.
Exchange | SHE |
---|---|
CurrencyCode | CNY |
ISIN | CNE100001JY4 |
Sector | Industrials |
Industry | Electrical Equipment & Parts |
Dividend Yield | 0.6% |
---|---|
Beta | -0.02 |
Market Cap | 7B |
PE Ratio | 76.14 |
Target Price | 34 |
Changshu Tianyin Electromechanical Co.,Ltd engages in the research and development, production, and sale of refrigerator compressor supporting parts in China. The company offers overheat overload protectors; PTC starter relays; junction boxes for various refrigeration appliances; current start relays; starter protectors; plastic suction silencers for various refrigerator compressors; plastic compression spring support seats; and refrigerator compressor inverter controllers. It also provides radar and aerospace electronics products, such as radar and electronic warfare technology, space technology, etc. The company was founded in 2002 and is based in Changshu, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 300342.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