-
1 Comment
SAMCO Inc is currently in a long term uptrend where the price is trading 1.1% above its 200 day moving average.
From a valuation standpoint, the stock is 66.2% more expensive than other stocks from the Technology sector with a price to sales ratio of 5.5.
SAMCO Inc's total revenue sank by 12.7% to $2B since the same quarter in the previous year.
Its net income has dropped by 4.2% to $243M since the same quarter in the previous year.
Based on the above factors, SAMCO Inc gets an overall score of 1/5.
| ISIN | JP3322950001 |
|---|---|
| Sector | Technology |
| Industry | Semiconductor Equipment & Materials |
| Exchange | TSE |
| CurrencyCode | JPY |
| Beta | 0.98 |
|---|---|
| Market Cap | 20B |
| PE Ratio | 13.44 |
| Target Price | 2840 |
| Dividend Yield | 3.6% |
SAMCO Inc. operates as a semiconductor and materials company. The company primarily offers thin film deposition, microfabrication, cleaning, and surface treatment products. Its deposition systems include atomic layer deposition systems, Plasma enhanced chemical vapor deposition (PECVD) systems, liquid source CVD systems, and diamond-like carbon coating systems; and etching systems comprise inductively coupled plasma (ICP), silicon deep reactive ion, reactive ion, and xenon difluoride etching systems. It also provides Aqua Plasma cleaner, a plasma processing equipment; plasma cleaners; and UV ozone cleaners. The company was formerly known as SAMCO International, Inc. and changed its name to SAMCO Inc. in December 2004. SAMCO Inc. was incorporated in 1979 and is headquartered in Kyoto, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 6387.TSE 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
