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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
undefined (S) Business Model and Operations Summary
SentinelOne, Inc. operates as a cybersecurity provider in the United States and internationally. The company's Extended Detection and Response (XDR) data stack that fuses together the data, access, control, and integration planes of endpoint protection platform, endpoint detection and response, cloud workload protection platform, and IoT security into a centralized platform. Its Singularity XDR Platform delivers an artificial intelligence-powered autonomous threat prevention, detection, and response capabilities across an organization's endpoints; and cloud workloads, which enables seamless and automatic protection against a spectrum of cyber threats. The company was formerly known as Sentinel Labs, Inc. and changed its name to SentinelOne, Inc. in March 2021. SentinelOne, Inc. was incorporated in 2013 and is headquartered in Mountain View, California.
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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