-
1 Comment
Daibochi Plastic & Packaging Industry Bhd is currently in a long term downtrend where the price is trading 8.3% below its 200 day moving average.
From a valuation standpoint, the stock is 79.8% cheaper than other stocks from the Other sector with a price to sales ratio of 1.3.
Daibochi Plastic & Packaging Industry Bhd's total revenue rose by 1.5% to $161M since the same quarter in the previous year.
Its net income has increased by 3.2% to $15M since the same quarter in the previous year.
Finally, its free cash flow fell by 58.6% to $8M since the same quarter in the previous year.
Based on the above factors, Daibochi Plastic & Packaging Industry Bhd gets an overall score of 3/5.
| Exchange | KLSE |
|---|---|
| CurrencyCode | MYR |
| Sector | Consumer Cyclical |
| Industry | Packaging & Containers |
| ISIN | MYL8125OO006 |
| Beta | 0.16 |
|---|---|
| Market Cap | 572M |
| Target Price | 3.9 |
| Dividend Yield | 4.6% |
| PE Ratio | 20.38 |
Scientex Packaging (Ayer Keroh) Berhad engages in the manufacture and marketing of flexible packaging materials in Malaysia, Australia, Thailand, Myanmar, Singapore, the Philippines, Myanmar, and internationally. It offers products for food and beverage, home care, personal care, pet care, and packaging sectors. The company was formerly known as Daibochi Berhad and changed its name to Scientex Packaging (Ayer Keroh) Berhad in December 2021. The company was incorporated in 1972 and is based in Melaka Pindah, Malaysia. Scientex Packaging (Ayer Keroh) Berhad is a subsidiary of Scientex Berhad.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 8125.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
