KenDUemura / options-trading-strategies-in-python-basic

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Learn A to Z of Algorithmic and Quantitative Trading

Quantra® is an e-learning portal by QuantInsti® that specializes in Algorithmic & Quantitative Trading. Quantra offers the best self-paced courses that are a mix of videos, audios, presentations, multiple choice questions and highly interactive exercises.



Made on Python version 2.7

Table of contents

About the course

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This course covers basic concepts, exercises, and practical implementation of five options trading strategies. It has a mix of videos, eBooks, MCQs, iPython notebook documents, and interactive coding exercises to enhance your learning experience.

What do I learn in this course

  • Fundamentals of options trading
  • Code and analyse the payoffs of put and call options
  • Understand how volatility plays an important role while trading in options and how to code historical volatility in python
  • Apply various types of options trading strategies like delta trading, hedging, and neutral strategies
  • Code the payoffs of these strategies in Python

Want to know more? Check out the course here.

Know Your Options

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This section contains a brief discussion about the various options that are available to a trader. This section also contains the python code to plot and visualize the payoff of these options.

The folder contains the following topics:

Put Option Payoff -- An Ipython notebook and an exercise to visualize the payoff of a Put Option. Call Option Payoff -- An Ipython notebook to visualize the payoff of a Call Option You can understand the concepts by accessing the full course.

Volatility

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This section contains a discussion on normal distribution and volatility and the coding of historical volatility in python.

The folder contains the following topics:

Historical Volatility -- An Ipython notebook and an interactive exercise to compute historical volatility of the stock. You can understand this topic in depth here.

Strategies

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This section covers some of the famous option trading strategies for different market scenarios. It also contains the code to create the strategies in python.

The folder contains the following topics:

Bull Call Spread: A bull call spread strategy is built by going long on call option and simultaneously selling a higher strike call option.

Bear Put Spread: A bear put spread strategy is built by going long on put option and simultaneously selling a lower strike put option.

Max_Loss.py: In this exercise, we calculate the payoff from the bull call spread and find the maximum possible profit that can be realized from it.

Protective Put: A protective put strategy is built by going long on stock and simultaneously buying a put option. The aim of this strategy is to protect from adverse stock movement.

Covered Call: A covered call strategy is built by going long on a stock and simultaneously selling a call option on that stock. The strategy is used when the view on the stock is neutral.

Download

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You can download the resources here.

Contact Us

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You can get in touch with us at quantra@quantinsti.com

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