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- SLG vs QFIN Comparison
SLG vs QFIN Comparison
Compare SLG & QFIN Stocks: Price Trends, ML Decisions, Charts, Trends, Technical Analysis and more.
- Machine Learning Prediction
- ML Decision
- SLG
- QFIN
- Stock Information
- Founded
- SLG 1980
- QFIN 2016
- Country
- SLG United States
- QFIN China
- Employees
- SLG N/A
- QFIN N/A
- Industry
- SLG Real Estate Investment Trusts
- QFIN Finance: Consumer Services
- Sector
- SLG Real Estate
- QFIN Finance
- Exchange
- SLG Nasdaq
- QFIN Nasdaq
- Market Cap
- SLG 4.5B
- QFIN 3.9B
- IPO Year
- SLG 1997
- QFIN 2018
- Fundamental
- Price
- SLG $72.40
- QFIN $25.86
- Analyst Decision
- SLG Hold
- QFIN Strong Buy
- Analyst Count
- SLG 14
- QFIN 1
- Target Price
- SLG $59.64
- QFIN $23.80
- AVG Volume (30 Days)
- SLG 571.3K
- QFIN 1.4M
- Earning Date
- SLG 10-16-2024
- QFIN 11-14-2024
- Dividend Yield
- SLG 4.10%
- QFIN 4.69%
- EPS Growth
- SLG N/A
- QFIN 25.79
- EPS
- SLG N/A
- QFIN 4.12
- Revenue
- SLG $900,932,000.00
- QFIN $2,351,728,381.00
- Revenue This Year
- SLG N/A
- QFIN $4.14
- Revenue Next Year
- SLG $5.64
- QFIN $3.31
- P/E Ratio
- SLG N/A
- QFIN $6.10
- Revenue Growth
- SLG N/A
- QFIN 9.80
- 52 Week Low
- SLG $28.55
- QFIN $13.68
- 52 Week High
- SLG $73.80
- QFIN $26.50
- Technical
- Relative Strength Index (RSI)
- SLG 68.75
- QFIN 61.52
- Support Level
- SLG $61.36
- QFIN $24.85
- Resistance Level
- SLG $71.31
- QFIN $25.39
- Average True Range (ATR)
- SLG 2.43
- QFIN 0.64
- MACD
- SLG 0.58
- QFIN -0.19
- Stochastic Oscillator
- SLG 85.85
- QFIN 46.36
About SLG SL Green Realty Corp
SL Green Realty is one of the largest Manhattan property owners and landlords, with interest in around 32 million square feet of wholly owned and joint-venture office space. The company has additional property exposure through its limited portfolio of well-located retail space. It operates as a real estate investment trust.
About QFIN Qifu Technology Inc.
Qifu Technology Inc is a Credit-Tech platform in China. It provides credit services more accessible and personalized to consumers and SMEs through Credit-Tech services to financial institutions, whereby it deploys its technology solutions to help financial institutions identify the diversified needs of consumers and SMEs, effectively access prospective borrowers that are creditworthy through multi-channels, enhance credit assessment on prospective borrowers, and manage credit risks and improve collection strategies and efficiency, among others.