-
1 Comment
Quilter plc is currently in a long term uptrend where the price is trading 2.4% above its 200 day moving average.
From a valuation standpoint, the stock is 98.6% cheaper than other stocks from the Financial Services sector with a price to sales ratio of 0.6.
Finally, its free cash flow grew by 134.7% to $244M since the same quarter in the previous year.
Based on the above factors, Quilter plc gets an overall score of 3/5.
Industry | Asset Management |
---|---|
Sector | Financial Services |
ISIN | None |
CurrencyCode | EUR |
Exchange | F |
Beta | 1.24 |
---|---|
Dividend Yield | 4.3% |
Target Price | None |
PE Ratio | 13.24 |
Market Cap | 2B |
Quilter plc provides advice-led investment solutions and investment platforms in the United Kingdom and internationally. It operates in two segments, High Net Worth and Affluent. The company offers financial advice for protection, mortgages, savings, investments, and pensions. It also provides Quilter Investment Platform, an investment platform for advice-based wealth management products and services; Quilter Investors, which offers investment solutions; and Quilter Financial Planning, a restricted and independent financial adviser network that provides mortgage and financial planning advice and financial solutions to individuals and businesses through a network of intermediaries. In addition, the company offers discretionary investment management services to high-net worth customers, charities, companies, and institutions through a network of branches. Quilter plc was incorporated in 2007 and is based in London, the United Kingdom.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 2FQ.F 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