Volatility Trading Analysis with Python . Read CBOE® and S&P 500 volatility strategies benchmark indexes and replicating funds data . Use Python to perform historical volatility trading analysis by installing related packages and running code on Python IDE . Estimate historical or realized volatility through close to close, Parkinson, Garman-Klass and Rogers-Satchell metrics . Measure market participants implied volatility through related volatility index . Explore volatility and asset returns correlation, volatility risk premium, volatility term structure and volatility skew patterns . Use the Python language to help you understand the volatility of futures prices and explore volatility and assets returns correlation . For more information on how to use Python, visit http://Python.org/volatility trading analysis .Authentication failed. Unique API key is not valid for this user.
Who this course is for:
- Undergraduates or postgraduates who want to learn about volatility trading analysis using Python programming language.
- Finance professionals or academic researchers who wish to deepen their knowledge in derivatives finance.
- Sophisticated investors with experience in financial derivatives who desire to research volatility trading strategies.
- This course is NOT about “get rich quick” trading strategies or magic formulas.
|File Name :||Volatility Trading Analysis with Python free download|
|Genre / Category:||Finance & Accounting|
|File Size :||4.67 gb|
|Publisher :||Diego Fernandez|
|Updated and Published:||06 Jun,2022|