-
1 Comment
Sa Sa International Holdings Limited is currently in a long term uptrend where the price is trading 33.5% above its 200 day moving average.
From a valuation standpoint, the stock is 66.9% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 1.6.
Sa Sa International Holdings Limited's total revenue sank by 31.7% to $1B since the same quarter in the previous year.
Its net income has dropped by 209.6% to $-129M since the same quarter in the previous year.
Finally, its free cash flow grew by 152.4% to $134M since the same quarter in the previous year.
Based on the above factors, Sa Sa International Holdings Limited gets an overall score of 3/5.
Exchange | HK |
---|---|
CurrencyCode | HKD |
ISIN | KYG7814S1021 |
Sector | Consumer Cyclical |
Industry | Specialty Retail |
Dividend Yield | 2.6% |
---|---|
PE Ratio | 12.0 |
Beta | 1.0 |
Market Cap | 2B |
Target Price | 0.92 |
Sa Sa International Holdings Limited, an investment holding company, engages in the retail and wholesale of cosmetic products in Hong Kong, Macau, Mainland China, Southeast Asia, and internationally. The company offers skincare, fragrance, make-up, body care, hair care, inner beauty, personal care, and health and fitness products, as well as beauty equipment under various brands. It is also involved in intellectual property rights and property holding, and charitable activities, as well as operates online business. In addition, it sells its products through retail stores and e-commerce platforms. Sa Sa International Holdings Limited was founded in 1978 and is headquartered in Chai Wan, Hong Kong.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 0178.HK 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