-
1 Comment
MRCB-Quill REIT is currently in a long term uptrend where the price is trading 1.9% above its 200 day moving average.
From a valuation standpoint, the stock is 8.2% cheaper than other stocks from the Other sector with a price to sales ratio of 5.9.
MRCB-Quill REIT's total revenue rose by 5.7% to $42M since the same quarter in the previous year.
Its net income has increased by 21.8% to $21M since the same quarter in the previous year.
Finally, its free cash flow grew by 14.3% to $29M since the same quarter in the previous year.
Based on the above factors, MRCB-Quill REIT gets an overall score of 5/5.
Exchange | KLSE |
---|---|
CurrencyCode | MYR |
ISIN | MYL5123TO003 |
Sector | Real Estate |
Industry | REIT - Office |
Market Cap | 921M |
---|---|
PE Ratio | 11.68 |
Target Price | 0.88 |
Beta | 0.17 |
Dividend Yield | 9.1% |
Sentral REIT is a commercial Real Estate Investment Trust (REIT), established through the restated trust deed dated 2 December 2019 and the supplemental deed dated 24 December 2020. Managed by Sentral REIT Management Sdn Bhd ("SRM"), the main thrust of Sentral REIT's activities includes acquiring and investing in commercial properties in Malaysia to provide unitholders with long-term and sustainable distribution of income and to achieve long-term growth in the net asset value per Unit. To-date, Sentral REIT owns 10 buildings comprising four in Cyberjaya, four in Kuala Lumpur, one in Petaling Jaya and one in Penang, valued at RM2.523 billion as at 31 December 2024.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 5123.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