-
1 Comment
Shi Shi Services Limited is currently in a long term downtrend where the price is trading 2.7% below its 200 day moving average.
From a valuation standpoint, the stock is 93.2% cheaper than other stocks from the Real Estate sector with a price to sales ratio of 0.4.
Shi Shi Services Limited's total revenue rose by 6.9% to $131M since the same quarter in the previous year.
Its net income has increased by 85.5% to $-381K since the same quarter in the previous year.
Finally, its free cash flow fell by 29.6% to $3M since the same quarter in the previous year.
Based on the above factors, Shi Shi Services Limited gets an overall score of 3/5.
Sector | Real Estate |
---|---|
CurrencyCode | HKD |
Exchange | HK |
Industry | Real Estate Services |
ISIN | KYG8109A1031 |
Target Price | None |
---|---|
PE Ratio | None |
Market Cap | 79M |
Dividend Yield | 0.0% |
Beta | 0.32 |
Shi Shi Services Limited, an investment holding company, provides property management services in Hong Kong and the People's Republic of China. The company operates through three segments: Provision of Property Management and Related Services; Properties Investment; and Money Lending Business. It offers security, repair and maintenance, cleaning, finance management, and administrative and legal support services to residential properties under the Kong Shum brand name. The company was formerly known as Heng Sheng Holdings Limited and changed its name to Shi Shi Services Limited in October 2018. The company was founded in 1984 and is headquartered in Central, Hong Kong. Shi Shi Services Limited is a subsidiary of Heng Sheng Capital Limited.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 8181.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 2024