-
1 Comment
Location Sciences Group PLC is currently in a long term uptrend where the price is trading 10.0% above its 200 day moving average.
From a valuation standpoint, the stock is 92.3% cheaper than other stocks from the Technology sector with a price to sales ratio of 2.0.
Location Sciences Group PLC's total revenue sank by 0.0% to $376K since the same quarter in the previous year.
Its net income has dropped by 0.0% to $-534K since the same quarter in the previous year.
Finally, its free cash flow grew by 46.8% to $-124K since the same quarter in the previous year.
Based on the above factors, Location Sciences Group PLC gets an overall score of 3/5.
Industry | Software-Application |
---|---|
Sector | Technology |
ISIN | GB00BGT36S19 |
CurrencyCode | GBP |
Exchange | LSE |
Beta | 0.65 |
---|---|
PE Ratio | None |
Dividend Yield | 0.0% |
Target Price | 5.47 |
Market Cap | 4M |
Location Sciences Group PLC operates as a data intelligence company in the United Kingdom and internationally. The company offers Verify, a proprietary verification platform that provides media-agnostic analysis, and authentication of the accuracy and quality of location-targeted advertising data to automotive, retail, quick service restaurant, grocery, consumer packaged goods, and travel and hospitality industries; and GeoProtect, a location data optimization and transparency platform. It serves advertisers, agencies, and suppliers. The company was formerly known as Proxama Plc and changed its name to Location Sciences Group PLC in March 2018. Location Sciences Group PLC was founded in 2005 and is based in Cheltenham, the United Kingdom.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for LSAI.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 2024