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

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

$12+
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Learn how to price options using Black-Scholes, use the greeks to manage risk, and make money by computing implied volatility.

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

Trying to decide if the guide is right for you?

Who, specifically, is this guide for?

The Ultimate Guide is for investors and traders who want to use Python for valuing plain vanilla, European-style, equity options. If you have an understanding of options - or want to learn about options - and are familiar with the Python programming language, this guide is for you.

Who should NOT buy this guide?

If you are a professional options trader or professional quantitative developer working at a hedge fund, this guide is probably not for you.

This guide is focused on laying the foundations of using Python to trade options, more profitably. It's the exact code I started with to make $1,100 per week trading options in my free time. This guide is not a "get rich quick" scheme. It's focused on teaching you how to price options and implied volatility with Python.

Some of the positive reviews for the Ultimate Guide

What You'll Learn Inside the Ultimate Guide

  • Understand the Important Jargon
  • What Are Options?
  • What Is the Black-Scholes Option Pricing Model?
  • Understand (Enough of) the Math
  • Code the Black-Scholes Formula
  • Understand the Greeks
  • Code the Greeks
  • Code Realized Volatility
  • Code Implied Volatility
  • Get Live 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

A Sneak Peek of Some of What You'll Learn

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.

FAQs

What do you mean live options data?

I use yfinance to pull options data from Yahoo Finance. The prices are generally updated from the exchange with a 20-minute delay. "Live" does not mean "real-time" or "streaming."

What all is included?

The Ultimate Guide includes the 46-page PDF ebook, associated Jupyter Notebooks, and cached options data.

Who, specifically, is this Ultimate Guide for?

The Ultimate Guide is for investors and traders who want to use Python for valuing equity options. If you have an understanding of options and are familiar with the Python programming language, this guide is for you.

Who should NOT buy this Ultimate Guide?

If you are a professional options trader or professional quantitative developer working at a hedge fund, this guide is probably not for you.

This guide is focused on laying the foundations of using Python to trade options, more profitably. It's the exact code I start with to make $1,100 per week trading options in my free time. This guide is not a "get rich quick" scheme. It's focused on teaching you how to price options and implied volatility with Python.

Does the Ultimate Guide come with Python Code?

Yes. All the Python code is included in two Jupyter Notebooks. The first uses cached options data. The second uses live options data.

Can I run this code on my own machine?

Yes. You need the Python scientific computing stack. Your best bet is to download and install the free Anaconda distribution.

What problems will the Ultimate Guide help me overcome?

The math is hard. Translating that math to Python code is harder. This Ultimate Guide gives you a head start with all the code already available.

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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
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