-
1 Comment
Enova International, Inc is currently in a long term uptrend where the price is trading 18.7% above its 200 day moving average.
From a valuation standpoint, the stock is 97.5% cheaper than other stocks from the Financial Services sector with a price to sales ratio of 1.1.
Enova International, Inc's total revenue sank by 0.9% to $264M since the same quarter in the previous year.
Its net income has increased by 556.3% to $231M since the same quarter in the previous year.
Finally, its free cash flow fell by 56.6% to $108M since the same quarter in the previous year.
Based on the above factors, Enova International, Inc gets an overall score of 3/5.
Exchange | F |
---|---|
CurrencyCode | EUR |
ISIN | US29357K1034 |
Industry | Credit Services |
Sector | Financial Services |
Market Cap | 2B |
---|---|
PE Ratio | 10.85 |
Target Price | 43.25 |
Beta | 1.35 |
Dividend Yield | None |
Enova International, Inc., a technology and analytics company, provides online financial services in the United States, Brazil, and internationally. The company provides installment loans; line of credit accounts; CSO programs, including arranging loans with independent third-party lenders and assisting in the preparation of loan applications and loan documents; and bank programs, such as marketing services and loan servicing for near-prime unsecured consumer installment loan. It offers money transfer services. It markets its financing products under the CashNetUSA, NetCredit, OnDeck, Headway Capital, Simplic, and Pangea names. The company was founded in 2003 and is headquartered in Chicago, Illinois.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 27E.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 2025