-
1 Comment
Shanghai Baolong Automotive Corporation is currently in a long term uptrend where the price is trading 8.3% above its 200 day moving average.
From a valuation standpoint, the stock is 76.7% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 1.2.
Shanghai Baolong Automotive Corporation's total revenue rose by 10.6% to $929M since the same quarter in the previous year.
Its net income has increased by 17.3% to $76M since the same quarter in the previous year.
Finally, its free cash flow grew by 13.7% to $-56M since the same quarter in the previous year.
Based on the above factors, Shanghai Baolong Automotive Corporation gets an overall score of 5/5.
Exchange | SHG |
---|---|
CurrencyCode | CNY |
ISIN | CNE100002X83 |
Sector | Consumer Cyclical |
Industry | Auto Parts |
Market Cap | 9B |
---|---|
Beta | 0.11 |
PE Ratio | 25.53 |
Target Price | 52.59 |
Dividend Yield | None |
Shanghai Baolong Automotive Corporation manufactures and sells automotive parts and components. It provides automotive rubber and metal parts, including traditional and tire pressure monitoring system valves; electronically controlled air suspension system; automotive metal tubing, such as exhaust pipes, EGR pipes, roof rail, and metal brackets; automotive structural parts; tire pressure monitoring system; automotive sensors, that includes pressure rain and light, speed and position, current, and accelerator sensors; intelligent drive solutions; and automotive aftermarket and equipment products. Shanghai Baolong Automotive Corporation was founded in 1997 and is headquartered in Shanghai, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 603197.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 2025