The 46-Page Ultimate Guide to Pricing Options and Implied Volatility With Python (PDF + code)

$8
$8
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This 46-page ultimate guide teaches you everything you need to start analyzing equity options with Python.

The guide contains both a PDF and a Jupyter Notebook file.

What you'll be able to do with this ultimate guide:

  • Understand the Important Jargon
  • Answer What Are Options?
  • Answer What Is the Black-Scholes Option Pricing Model?
  • Understand (Some of) the Math
  • Code Black-Scholes Formula in Python
  • Understand The Greeks
  • Code the Greeks in Python
  • Code Realized Volatility
  • Code Implied Volatility
  • Get Real Options Market Data
  • Compute Implied Volatility
  • Interpolate Missing and Bad Implied Volatility Values
  • Compute Black-Scholes and the Greeks
  • Analyze the Model Error
  • Analyze Implied Volatility

Build the famous hockey stick charts for any position.

Compute the value of an option using Black-Scholes.

Compute the rolling historical volatility of an underlying.

Compute and analyze model error.

Build the implied volatility skew and term structure.

Plot the 3D volatility surface chart.


  • Includes 46-page PDF, Jupyter Notebook file, cached data file

  • Python libraries used
    Pandas, NumPy, SciPy, Matplotlib, Jupyter Notebook
  • What you'll learn
    How to calculate and plot option payoffs, code the Black-Scholes pricing formula and greeks, compute implied volatility, analyze implied volatility and more...
  • Support
    @pyquantnews
  • Includes 46-page PDF, Jupyter Notebook file, cached data file
  • Python libraries usedPandas, NumPy, SciPy, Matplotlib, Jupyter Notebook
  • What you'll learnHow to calculate and plot option payoffs, code the Black-Scholes pricing formula and greeks, compute implied volatility, analyze implied volatility and more...
  • Support@pyquantnews
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The 46-Page Ultimate Guide to Pricing Options and Implied Volatility With Python (PDF + code)

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