An Introduction to Barrier Options

In this post we will take a cursory look at exotic products and how banks market them to customers. Most of the innovations have been on the options side as swaps have only recently developed into non-financial areas.

Options are now classified into two broad categories:

  1. Path independent (European options);
  2. Path Dependent (American and Exotic options)

A common type of path dependent option is known as a barrier option. Barrier options resemble American options since their value depends on how underlying asset behaves over time. But they are simpler to value than American options since the critical barrier of the underlying asset price is determined and specified in advance.

There are two broad classes of barrier options:

  1. Extinguishable or knock out options
  2. Exercisable or knock-in options

Extinguishable or Knock Out Options

An extinguishable or knockout option is operational from the start but disappears as soon the spot rate of the underlying asset reaches a certain predetermined level or barrier. This event can happen at anytime throughout the life of the option.

There are two main knock-out options:

  1. The up and out put
  2. The down and out call

Exercisable or knock-in (in) options

An exercisable or knock-in barrier option is an option that does not exist from inception, though a premium is paid up-front to the seller. The option is exercised, created or ‘in’ when the underlying asset reaches a certain predetermined level or barrier. This event can happen any time throughout the life of the option.

There are two main types of knock in options:

  1. The up and in put
  2. The down and in call

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Data Science in Finance: 9-Book Bundle

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Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

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