-
1 Comment
Urban&Civic plc is currently in a long term uptrend where the price is trading 27.8% above its 200 day moving average.
From a valuation standpoint, the stock is 85.1% cheaper than other stocks from the Real Estate sector with a price to sales ratio of 8.7.
Urban&Civic plc's total revenue sank by 0.0% to $36M since the same quarter in the previous year.
Its net income has dropped by 0.0% to $4M since the same quarter in the previous year.
Finally, its free cash flow grew by 73.4% to $-424K since the same quarter in the previous year.
Based on the above factors, Urban&Civic plc gets an overall score of 3/5.
Exchange | LSE |
---|---|
CurrencyCode | GBP |
ISIN | GB00BKT04W07 |
Sector | Real Estate |
Industry | Real Estate - Diversified |
Beta | 1.82 |
---|---|
Market Cap | 500M |
PE Ratio | 64.62 |
Target Price | 378.2 |
Dividend Yield | 0.0% |
Urban&Civic plc engages in the property development and investment activities in the United Kingdom. The company operates in three segments: Strategic Sites, Land Promotion, and Commercial Property Development. Its strategic sites and land promotion portfolio include serviced and unserviced lands, consented and unconsented lands, and mixed-use development and promotion sites. The company also develops city center and commercial regional projects; and provides property management, administration, and project co-ordination and management services. It primarily serves house builders and commercial customers. The company was incorporated in 1994 and is headquartered in London, the United Kingdom.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for UANC.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