MVIS
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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 (MVIS) Business Model and Operations Summary
MicroVision, Inc. develops lidar sensors used in automotive safety and autonomous driving applications. Its laser beam scanning technology is based on micro-electrical mechanical systems, laser diodes, opto-mechanics, electronics, algorithms, and software. The company also develops micro-display concepts and designs for head-mounted augmented reality (AR) headsets, as well as 1440i MEMS module that can support AR headsets; Interactive Display modules used in smart speakers and other devices; and Consumer Lidar used in smart home systems. In addition, it provides PicoP, a scanning technology that creates full color, high-contrast, and uniform image over the entire field-of-view from a small and thin module. Further, the company develops 1st generation long range lidar. The company sells its products primarily to original equipment manufacturers and original design manufacturers. MicroVision, Inc. was founded in 1993 and is headquartered in Redmond, Washington.
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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