-
1 Comment
Keli Sensing Technology (Ningbo) Co.,Ltd is currently in a long term downtrend where the price is trading 27.3% below its 200 day moving average.
From a valuation standpoint, the stock is 6.7% more expensive than other stocks from the Industrials sector with a price to sales ratio of 5.4.
Keli Sensing Technology (Ningbo) Co.,Ltd's total revenue rose by 15.8% to $230M since the same quarter in the previous year.
Its net income has increased by 14.0% to $60M since the same quarter in the previous year.
Finally, its free cash flow fell by 35.8% to $35M since the same quarter in the previous year.
Based on the above factors, Keli Sensing Technology (Ningbo) Co.,Ltd gets an overall score of 2/5.
ISIN | CNE100003M02 |
---|---|
Industry | Electrical Equipment & Parts |
CurrencyCode | CNY |
Exchange | SHG |
Sector | Industrials |
Market Cap | 5B |
---|---|
Beta | 0.37 |
PE Ratio | 23.07 |
Target Price | None |
Dividend Yield | 1.7% |
Keli Sensing Technology (Ningbo) Co.,Ltd., together with its subsidiaries, engages in the research and development, manufacture, and sale of various types of sensors, weighing indicators, electronic weighing systems, system integration and health scales in China and internationally. It offers beam, single point, S-type, canister, tension, digital, and other load cells, as well as weigh modules; force transducers; and digital, analog signal, bench and floor scale, and control indicators, as well as remote displays and amplifiers, as well as junction boxes, pressure transducers, Internet of Things, and flow meters. The company was founded in 2002 and is headquartered in Ningbo, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 603662.SHG 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 2024