-
1 Comment
AA plc is currently in a long term uptrend where the price is trading 9.9% above its 200 day moving average.
From a valuation standpoint, the stock is 95.8% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 0.2.
Based on the above factors, AA plc gets an overall score of 2/5.
Exchange | LSE |
---|---|
CurrencyCode | GBP |
ISIN | GB00BMSKPJ95 |
Sector | Consumer Cyclical |
Industry | Personal Services |
PE Ratio | 2.99 |
---|---|
Target Price | 119 |
Dividend Yield | 0.0% |
Market Cap | 218M |
Beta | 2.5 |
AA plc provides roadside assistance, insurance, and driving services in the United Kingdom. It operates through two segments, Roadside and Insurance. The company offers breakdowns cover for cars, motorcycles, caravans, vans, and towing; car, motorbike, van, and caravan insurance; and loans, savings, mortgage, travel currency card, insurance, and credit card products. It also provides home, content, building, pet, and holiday home insurance products; and travel services. In addition, the company offers driving advisory services, such as child safety, fuel and environment, legal advisory, service and repair, safety, security, and driving cost and other services; car and MOT services; and financial services, such as personal loans, car loans, home improvement loans, debt consolidation loans, wedding loans, loan management, savings, credit cards, and online security services, as well as reinsurance services. It serves fleet and leasing companies. The company was founded in 1905 and is headquartered in Basingstoke, the United Kingdom.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for AA.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