-
1 Comment
Saga plc is currently in a long term uptrend where the price is trading 22.4% above its 200 day moving average.
From a valuation standpoint, the stock is 99.1% cheaper than other stocks from the Financial Services sector with a price to sales ratio of 0.5.
Based on the above factors, Saga plc gets an overall score of 2/5.
ISIN | GB00BMX64W89 |
---|---|
Exchange | LSE |
CurrencyCode | GBP |
Industry | Insurance - Diversified |
Sector | Financial Services |
Market Cap | 254M |
---|---|
PE Ratio | None |
Target Price | 196.667 |
Beta | 2.41 |
Dividend Yield | None |
Saga plc, together with its subsidiaries, provides package and cruise holidays, general insurance, and personal finance products and services in the United Kingdom. It operates through three segments: Travel, Insurance, and Other Businesses and Central Costs. The company offers travel, motor, home, private medical, and other insurance products. It also operates and delivers ocean and river cruise holidays, as well as package tour and other holiday products; and provides savings accounts, equity release, legal services, mortgages, and investment products and services. In addition, the company is involved in mailing house; research and insight analysis; provision of insurance broking, repair of automotive vehicles, debt service, motor accident management, and printing and mailing services; Saga Money which offers personal finance products; and Saga Publishing business. The company was founded in 1950 and is headquartered in London, the United Kingdom.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for SAGA.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