-
1 Comment
UMS Neiken Group Bhd is currently in a long term uptrend where the price is trading 27.6% above its 200 day moving average.
From a valuation standpoint, the stock is 81.3% cheaper than other stocks from the Other sector with a price to sales ratio of 1.2.
UMS Neiken Group Bhd's total revenue rose by 33.6% to $21M since the same quarter in the previous year.
Its net income has increased by 221.7% to $2M since the same quarter in the previous year.
Finally, its free cash flow fell by 66.6% to $486K since the same quarter in the previous year.
Based on the above factors, UMS Neiken Group Bhd gets an overall score of 4/5.
Sector | Industrials |
---|---|
Industry | Electrical Equipment & Parts |
Exchange | KLSE |
CurrencyCode | MYR |
ISIN | MYL7227OO001 |
Dividend Yield | 3.5% |
---|---|
Beta | 0.43 |
Market Cap | 68M |
PE Ratio | 12.43 |
Target Price | None |
UMS-Neiken Group Berhad, an investment holding company, designs, manufactures, distributes, and trades in electrical wiring accessories and related electrical products in Malaysia, Vietnam, and Singapore. The company offers switches, sockets, adaptors, and waterproof covers, as well as plugs top, round pin plugs, and AC magnetic starter. It also trades in, imports, and exports various electrical products; and manufactures, assembles, wholesales, trades in, imports, and exports electrical fittings and wiring accessories, as well as provides related repair services. The company was incorporated in 2004 and is based in Rawang, Malaysia. UMS-Neiken Group Berhad is a subsidiary of United MS Holdings Sdn. Bhd.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 7227.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