-
1 Comment
Time Finance plc is currently in a long term uptrend where the price is trading 19.2% above its 200 day moving average.
From a valuation standpoint, the stock is 98.7% cheaper than other stocks from the Financial Services sector with a price to sales ratio of 0.7.
Time Finance plc's total revenue sank by 0.0% to $8M since the same quarter in the previous year.
Its net income has dropped by 0.0% to $1M since the same quarter in the previous year.
Finally, its free cash flow grew by 28.8% to $926K since the same quarter in the previous year.
Based on the above factors, Time Finance plc gets an overall score of 3/5.
ISIN | GB00BCDBXK43 |
---|---|
Sector | Financial Services |
Industry | Credit Services |
CurrencyCode | GBP |
Exchange | LSE |
Beta | 1.88 |
---|---|
Market Cap | 22M |
Target Price | 91 |
PE Ratio | 14.12 |
Dividend Yield | 4.3% |
Time Finance plc, together with its subsidiaries, provides financial products and services to consumers and businesses in the United Kingdom. It operates through four segments: Asset Finance, Vehicle Finance, Loan Finance, and Invoice Finance. The company offers lease finance and hire purchase services, cash flow finance and business funding services, and business loans to small and medium-sized enterprises. It also provides mortgages, secured loans, bridging finance, and commercial and property lending services, as well as factoring services. The company was formerly known as 1pm plc and changed its name to Time Finance plc in December 2020. Time Finance plc was founded in 2000 and is based in Bath, the United Kingdom.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for OPM.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