Ansys ANSS
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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
Ansys (ANSS) Business Model and Operations Summary
ANSYS, Inc. develops and markets engineering simulation software and services worldwide. It offers ANSYS Workbench, a framework upon which its multiphysics engineering simulation technologies are built and enables engineers to simulate the interactions between structures, heat transfer, fluids, electronics, and optical elements in a unified engineering simulation environment; high-performance computing product suite; power analysis and optimization software suite that manages the power budget, power delivery integrity, and power-induced noise in an electronic design; and structural analysis product suite that provides simulation tools for product design and optimization. The company also provides electronics product suite that offers field simulation software for designing electronic and electromechanical products; SCADE product suite, a solution for embedded software simulation, code production, and automated certification; fluids product suite that enables modeling of fluid flow and other related physical phenomena; Ansys Granta products to give access to material intelligence; photonic design and simulation tools; and optical sensor and closed-loop, and real-time simulation, as well as safety-certified embedded software solutions. In addition, the company provides Discovery product family for use in the simulation of product design; and academic product suite used in research and teaching settings, which allows students to become familiar with its simulation software. It serves engineers, designers, researchers, and students in the aerospace and defense, automotive transportation and mobility, construction, consumer products, energy, healthcare, high-tech, industrial equipment, materials and chemical processing, and sports industries. The company was founded in 1970 and is headquartered in Canonsburg, Pennsylvania.
Key Insights
Ansys (ANSS) Core Market Data and Business Metrics
Latest Closing Price
$347.87Market Cap
$28.66 BillionAverage Trade Volume
511,456 SharesTotal Outstanding Shares
87.92 Million SharesCEO
Dr. Ajei S. Gopal Ph.D.Total Employees
6,500IPO Date
June 20, 1996SIC Description
Services-prepackaged SoftwarePrimary Exchange
NASDAQHeadquarters
2600 Ansys Drive, Southpointe, Canonsburg, PA, 15317
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
Short Interest
Short Interest
This information represents bi-monthly aggregated short interest data reported to the Financial Industry Regulatory Authority (FINRA) by broker-dealers.
Settlement Date: The date on which the short interest data is considered settled, typically based on exchange reporting schedules.
Short Interest: The total number of shares that have been sold short but have not yet been covered or closed out.
Avg Daily Volume: The average daily trading volume for the stock over the specified period, typically used to contextualize short interest.
Days To Cover: The estimated number of days it would take to cover all short positions based on average trading volume.
Bi-monthly short interest levels can be used to gauge bearish market sentiment and short squeeze potential
Revenue Breakdown
Distribution of revenue across unique business segments & geographies
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Historical Stock Splits
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Historical Dividends
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No historical dividends |