-
1 Comment
SAIC Motor Corporation Limited is currently in a long term downtrend where the price is trading 3.5% below its 200 day moving average.
From a valuation standpoint, the stock is 94.2% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 0.3.
SAIC Motor Corporation Limited's total revenue sank by 4.2% to $243B since the same quarter in the previous year.
Its net income has dropped by 21.4% to $4B since the same quarter in the previous year.
Finally, its free cash flow fell by 115.2% to $-2B since the same quarter in the previous year.
Based on the above factors, SAIC Motor Corporation Limited gets an overall score of 1/5.
| Exchange | SHG |
|---|---|
| CurrencyCode | CNY |
| ISIN | CNE000000TY6 |
| Sector | Consumer Cyclical |
| Industry | Auto Manufacturers |
| Target Price | 15.26 |
|---|---|
| Dividend Yield | 2.0% |
| Beta | 0.27 |
| Market Cap | 149B |
| PE Ratio | 14.54 |
SAIC Motor Corporation Limited engages in the research and development, production, and sale of vehicles and their parts in the China and internationally. The company operates through Vehicles & Components and Financial Services segments. Its Vehicles & Components segment produces and sells complete vehicles and components. The Financial Services segment engages in financial services. SAIC Motor Corporation Limited was founded in 1997 and is based in Shanghai, the People's Republic of China. SAIC Motor Corporation Limited is a subsidiary of Shanghai Automotive Industry Corporation (Group) Corp.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 600104.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 2026