loanDepot LDI
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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
loanDepot (LDI) Business Model and Operations Summary
loanDepot Inc provides nonbank consumer lending solutions for individuals in the United States. It offers personal, residential home, home refinancing, mortgage and home equity loans. It also provides online mortgage loans for refinancing and home purchases. It serves customers through distribution channels, including consumer direct centres, retail branches, wholesale centres, and consumer finance and servicing centres in the United States. It competes with commercial banks and financial institutions.
Key Insights
loanDepot (LDI) Core Market Data and Business Metrics
Latest Closing Price
$1.31Market Cap
$262.13 MillionTotal Outstanding Shares
111.01 Million SharesTotal Employees
4,547IPO Date
February 11, 2021SIC Description
Finance ServicesPrimary Exchange
New York Stock ExchangeHeadquarters
6561 Irvine Center Drive, Irvine, CA, 92618
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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