-
1 Comment
Dingyi Group Investment Limited is currently in a long term uptrend where the price is trading 11.1% above its 200 day moving average.
From a valuation standpoint, the stock is 80.4% cheaper than other stocks from the Financial Services sector with a price to sales ratio of 2.9.
Dingyi Group Investment Limited's total revenue rose by 42.0% to $134M since the same quarter in the previous year.
Its net income has increased by 135.6% to $72M since the same quarter in the previous year.
Finally, its free cash flow grew by 33.2% to $-41M since the same quarter in the previous year.
Based on the above factors, Dingyi Group Investment Limited gets an overall score of 5/5.
Exchange | HK |
---|---|
CurrencyCode | HKD |
Sector | Financial Services |
Industry | Credit Services |
ISIN | BMG2763D1074 |
PE Ratio | None |
---|---|
Market Cap | 234M |
Target Price | None |
Beta | 0.62 |
Dividend Yield | None |
Dingyi Group Investment Limited, an investment holding company, engages in the loan financing and financial leasing businesses in Mainland China and Hong Kong. The company operates through three segments: Securities Trading Business; Loan Financing Business; and Properties Development Business. It is also involved in the securities trading and properties development businesses. In addition, the company engages in the wine trading; investment advisory; and other businesses. The company was formerly known as Chevalier Pacific Holdings Limited and changed its name to Dingyi Group Investment Limited in February 2012. Dingyi Group Investment Limited was incorporated in 1989 and is based in Wan Chai, Hong Kong.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 0508.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