Kaixin KXIN
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Relative Strength Index (RSI)
- The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. It is typically used to identify overbought or oversold conditions in financial markets.
- The RSI is calculated using the following formula:
RSI = 100 - (100 / (1 + RS))
Where RS is the ratio of the average gains to the average losses over a specified period.
- The default time period used is 14 days.
- RSI values range between 0 and 100.
RSI values above 70 are considered overbought (indicating a potentially opportune time to sell)
RSI values below 30 are considered oversold (indicating a potentially opportune time to buy)
RSI is not a perfect indicator and should be used in conjunction with other technical analysis tools, this is for informational purposes only and is not a substitute for professional financial advice.
About
Kaixin (KXIN) Business Model and Operations Summary
Kaixin Holdings is an auto retail platform for luxury used cars and imported new cars. The company is actively engaged in the research and development, design, manufacturing, and sales of electric vehicles and promotes the innovation of next-generation autonomous driving and artificial intelligence technologies. The company generates revenues from sales of used cars, as well as fees obtained from its role as a channel partner for third-party auto financing and other value-added service providers.
Key Insights
Kaixin (KXIN) Core Market Data and Business Metrics
Latest Closing Price
$0.95Market Cap
$10.51 MillionTotal Outstanding Shares
8.85 Million SharesTotal Employees
19IPO Date
November 6, 2017SIC Description
Retail-auto Dealers & Gasoline StationsPrimary Exchange
NASDAQHeadquarters
5f, North Wing, Chaoyang District, Beijing, F4, 100016
Earnings Reports
Expected vs. Actual Quarterly Earnings-Per-Share & Revenue
Short Volume
Daily short volume activity identifies short-term trading pressure and potential price volatility
Revenue Breakdown
Distribution of revenue across unique business segments & geographies
Historical Stock Splits
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