-
1 Comment
Thriven Global Berhad is currently in a long term downtrend where the price is trading 7.6% below its 200 day moving average.
From a valuation standpoint, the stock is 89.1% cheaper than other stocks from the Other sector with a price to sales ratio of 0.7.
Thriven Global Berhad's total revenue rose by 18.5% to $49M since the same quarter in the previous year.
Its net income has increased by 35.0% to $7M since the same quarter in the previous year.
Finally, its free cash flow grew by 185.0% to $20M since the same quarter in the previous year.
Based on the above factors, Thriven Global Berhad gets an overall score of 4/5.
Exchange | KLSE |
---|---|
CurrencyCode | MYR |
ISIN | MYL7889OO008 |
Sector | Real Estate |
Industry | Real Estate - Diversified |
Market Cap | 49M |
---|---|
Beta | 0.45 |
PE Ratio | 1.8 |
Target Price | None |
Dividend Yield | None |
Thriven Global Berhad, an investment holding company, develops and invests in properties in Malaysia. It operates through Property Development, Property Investment, Food and Beverages, and Investment Holding and Others segments. The company also offers hospitality, retail management, property ownership and management, and maintenance and facilities management services, as well as engages in the food and beverage and parking facilities operations. In addition, it operates household goods and groceries, convenience stores, mini market, and supermarket. The company was formerly known as Mulpha Land Berhad and changed its name to Thriven Global Berhad in June 2015. Thriven Global Berhad was incorporated in 1989 and is headquartered in Petaling Jaya, Malaysia.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 7889.KLSE 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