-
1 Comment
Camellia Plc is currently in a long term downtrend where the price is trading 3.8% below its 200 day moving average.
From a valuation standpoint, the stock is 100.0% cheaper than other stocks from the Consumer Defensive sector with a price to sales ratio of 0.7.
Based on the above factors, Camellia Plc gets an overall score of 1/5.
Exchange | LSE |
---|---|
CurrencyCode | GBP |
ISIN | GB0001667087 |
Industry | Farm Products |
Sector | Consumer Defensive |
Market Cap | 112M |
---|---|
PE Ratio | None |
Beta | 0.34 |
Target Price | 20000 |
Dividend Yield | None |
Camellia Plc, together with its subsidiaries, engages in agriculture and engineering business in the United Kingdom, Bangladesh, India, Kenya, Malawi, South Africa, North America, and South America. The company produces and manufactures instant tea, branded tea, and tea lounges; macadamia nuts, avocado, and other fruits, such as apples, pears, stone fruit, blueberries, plums, cherries, and grapes; and forestry, arable, rubber, and livestock products. It also provides various engineering workshop services comprising repair and manufacture of blow out preventers, offshore equipment, and metal finishing services, as well as maintenance for the onshore hydroelectric sector. In addition, the company invests in listed securities; commercial and residential properties; collections of art, philately, and manuscripts. The company was incorporated in 1889 and is headquartered in Wrotham, the United Kingdom. Camellia Plc is a subsidiary of Camellia Holding AG.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for CAM.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