Synaptics SYNA
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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
Synaptics (SYNA) Business Model and Operations Summary
Synaptics Inc is a producer of semiconductor solutions for the mobile, PC, and Internet of Things markets. The company develops human interface solutions that enable touch, display, fingerprint, video, audio, voice, AI, and connectivity functions for smartphones, PCs, Internet of Things products, and other electronic devices. Geographically, it derives a majority of revenue from China. The company operates in one segment: the development, marketing, and sale of semiconductor products used in electronic devices and products.
Key Insights
Synaptics (SYNA) Core Market Data and Business Metrics
Latest Closing Price
$58.76Market Cap
$2.32 BillionTotal Outstanding Shares
38.55 Million SharesTotal Employees
1,716IPO Date
January 28, 2002SIC Description
Semiconductors & Related DevicesPrimary Exchange
NASDAQHeadquarters
1109 Mckay Drive, San Jose, CA, 95131-1706
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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