-
1 Comment
Chamberlin plc is currently in a long term uptrend where the price is trading 16.6% above its 200 day moving average.
From a valuation standpoint, the stock is 100.0% cheaper than other stocks from the Industrials sector with a price to sales ratio of 0.0.
Based on the above factors, Chamberlin plc gets an overall score of 2/5.
Exchange | LSE |
---|---|
CurrencyCode | GBP |
ISIN | GB0001870228 |
Industry | Specialty Industrial Machinery |
Sector | Industrials |
Market Cap | 2M |
---|---|
PE Ratio | 0.0 |
Target Price | 166 |
Beta | 0.41 |
Dividend Yield | None |
Chamberlin plc, together with its subsidiaries, manufactures and sells iron castings and engineered products in the United Kingdom, Italy, Germany, rest of Europe, and internationally. It operates through two segments, Foundries and Engineering. The company offers grey iron castings for the automotive sector, hydraulic, and mechanical engineering applications; cast iron radiators and consumer products in fitness and cookware markets; and grey, ductile, and alloyed iron castings for a range of applications, including power generation, renewable energy, bearing housings, steelworks, construction, and compressors. It also manufactures and sells lighting products for use in hazardous and explosive environments and other industrial applications; and provides cable management products. The company was formerly known as Chamberlin & Hill and changed its name to Chamberlin plc in 2007. Chamberlin plc was founded in 1890 and is headquartered in Walsall, the United Kingdom.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for CMH.LSE 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