Lecture 15 - Forward and Futures Markets

To begin the lecture, Professor Shiller elaborates on the difference between forwards and futures and on the role of futures markets to infer future prices for the underlying commodity or financial asset. Generalizing the discussion beyond futures markets to derivatives markets, he assesses the issue of speculation in those markets and its impact on capitalist activity. Subsequently, he introduces the notions of counterparty risk, standardization of contracts, and clearinghouses within the framework of the first futures market, the market for rice futures in Dojima, Japan.

While describing wheat futures, he addresses the price patterns of contango and backwardation, margin accounts that help alleviating counterparty risk, as well as the fair value formula for futures prices. The third commodity futures market is the oil futures market, which leads to description of the history of the oil market in general from the 1870s, to the first and second oil crisis, until the oil price spike in 2008.
Professor Shiller concludes this lecture with financial futures, specifically S&P 500 index futures, touching upon the difference between physical delivery and cash settlement.

1. Forwards vs. Futures Contracts; Speculation in Derivative Markets
2. The First Futures Market and the Role of Standardization
3. Rice Futures and Contango vs. Backwardation
4. Counterparty Risk and Margin Accounts
5. Wheat Futures and the Fair Value Formula for Futures Pricing
6. Oil Futures
7. The History of the Oil Market
8. Financial Futures and the Difficulty of Forecasting

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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.