-
1 Comment
Pressure Technologies plc is currently in a long term uptrend where the price is trading 5.8% above its 200 day moving average.
From a valuation standpoint, the stock is 99.9% cheaper than other stocks from the Energy sector with a price to sales ratio of 0.7.
Pressure Technologies plc's total revenue rose by 101.4% to $14M since the same quarter in the previous year.
Its net income has dropped by 591.5% to $-1M since the same quarter in the previous year.
Finally, its free cash flow grew by 94.3% to $-106K since the same quarter in the previous year.
Based on the above factors, Pressure Technologies plc gets an overall score of 4/5.
| Exchange | LSE |
|---|---|
| CurrencyCode | GBP |
| Sector | Energy |
| Industry | Oil & Gas Equipment & Services |
| ISIN | GB00B1XFKR57 |
| Beta | 1.53 |
|---|---|
| Market Cap | 13M |
| PE Ratio | None |
| Target Price | 50 |
| Dividend Yield | None |
Chesterfield Special Cylinders Holdings Plc, through its subsidiaries, design, manufactures, and reconditions high pressure gas cylinders. The company also provides integrity management services for safety-critical applications in defence, oil and gas, industrial, and hydrogen energy markets. It operates in the United Kingdom, France, Norway, the United States, Italy, Germany, Australia, Rest of Europe, and internationally. Chesterfield Special Cylinders Holdings Plc was formerly known as Pressure Technologies plc and changed its name to Chesterfield Special Cylinders Holdings Plc in March 2025. Chesterfield Special Cylinders Holdings Plc was founded in 1897 and is headquartered in Sheffield, the United Kingdom.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for PRES.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
