Lecture 17 - Options Markets

After introducing the core terms and main ideas of options in the beginning of the lecture, Professor Shiller emphasizes two purposes of options, a theoretical and a behavioral purpose.

Subsequently, he provides a graphical representation for the value of a call and a put option, and, in this context, addresses the put-call parity for European options. Within the framework of the Binomial Asset Pricing model, he derives the value of a call-option from the no-arbitrage-principle, and, as a continuous-time analogue to this formula, he presents the Black-Scholes Option Pricing formula. He contrasts implied volatility, as represented by the VIX index of the Chicago Board Options Exchange, which uses a different formula in the spirit of Black-Scholes, with the actual S&P Composite volatility from 1986 until 2010.

Professor Shiller concludes the lecture with some thoughts about options on single-family homes that he launched with his colleagues of the Chicago Mercantile Exchange in 2006.

1. Examples of Options Markets and Core Terms
2. Purposes of Option Contracts
3. Quoted Prices of Options and the Role of Derivatives Markets
4. Call and Put Options and the Put-Call Parity
5. Boundaries on the Price of a Call Option
6. Pricing Options with the Binomial Asset Pricing Model
7. The Black-Scholes Option Pricing Formula
8. Implied Volatility - The VIX Index in Comparison to Actual Market Volatility
9. The Potential for Options in the Housing Market

https://www.youtube.com/watch?v=VkUEWUxI6u0

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

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

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.