-
1 Comment
Qudian Inc is currently in a long term uptrend where the price is trading 2.2% 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.
Qudian Inc's total revenue sank by 56.0% to $849M since the same quarter in the previous year.
Its net income has increased by 363.2% to $592M since the same quarter in the previous year.
Based on the above factors, Qudian Inc gets an overall score of 3/5.
| Exchange | F |
|---|---|
| CurrencyCode | EUR |
| ISIN | US7477981069 |
| Sector | Financial Services |
| Industry | Credit Services |
| Dividend Yield | None |
|---|---|
| PE Ratio | 11.43 |
| Beta | 0.88 |
| Target Price | 1.69 |
High Templar Tech Limited operates as a consumer-oriented financial technology service company in the People's Republic of China. The company provides aircraft leasing; technology development and services; and research and development services. It provides financial institutions with a financial technology business management system consisting of a core service system group, a user identification and risk management system group, a payment and finance group, system platform support, a BI system group, and an intelligent monitoring system. It also offers full-process technical services and full-scenario precision marketing services to financial institutions. The company was formerly known as Qudian Inc. and changed its name to High Templar Tech Limited in December 2025. High Templar Tech Limited was founded in 2014 and is headquartered in Xiamen, China.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 1QU.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 2026