Sangoma Technologies SANG
$
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
Sangoma Technologies (SANG) Business Model and Operations Summary
Sangoma Technologies Corp is a provider of hardware and software components that enable or enhance Internet Protocol Communications Systems for both telecom and datacom applications. It is engaged in the development, manufacturing, distribution, and support of voice and data connectivity components for software-based communication applications. Its product includes data and telecom boards for media and signal processing, as well as gateway appliances and software. The Company sells into two geographic centers: USA and Other countries. Key revenue is generated from USA.
Key Insights
Sangoma Technologies (SANG) Core Market Data and Business Metrics
Latest Closing Price
$5.48Market Cap
$190.98 MillionTotal Outstanding Shares
33.51 Million SharesTotal Employees
671IPO Date
October 5, 2001Primary Exchange
NASDAQ
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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