-
1 Comment
Ningbo Donly Co.,Ltd is currently in a long term downtrend where the price is trading 24.5% below its 200 day moving average.
From a valuation standpoint, the stock is 7.1% cheaper than other stocks from the Industrials sector with a price to sales ratio of 4.7.
Ningbo Donly Co.,Ltd's total revenue rose by 30.7% to $323M since the same quarter in the previous year.
Its net income has increased by 1746.5% to $302M since the same quarter in the previous year.
Finally, its free cash flow fell by 58.0% to $18M since the same quarter in the previous year.
Based on the above factors, Ningbo Donly Co.,Ltd gets an overall score of 3/5.
Ningbo Donly Co.,Ltd engages in the research and development, manufacture, sale, and technical consultation of transmission equipment, door control systems, and industrial automatic control systems in China and internationally. The company provides gear motor, general gearbox, robot joint module, industry specific gearbox, integrated transmission device, asynchronous motor, explosion proof motor, permanent magnet motor, accessories. It offers its products for metallurgy, grain machinery, construction machinery, mining, rubber and plastic, electricity, light industry, logistics, new energy, chemical, water conservancy, lifting, building material, port, and environmental protection solutions. Ningbo Donly Co.,Ltd was formerly known as Ningbo Donly Transmission Equipment Co., Ltd. and changed its name to Ningbo Donly Co.,Ltd in January 2014. The company was founded in 1993 and is headquartered in Ningbo, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 002164.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