Insurance, the Archetypal Risk Management Institution

In the beginning of the lecture, Professor Shiller talks about risk pooling as the fundamental concept of insurance, followed by references to moral hazard and selection bias as prominent problems of the insurance industry. In order to provide an explicit example from the insurance industry, he elaborates on the story behind American International Group (AIG), from its creation by Cornelius Vander Starr in Shanghai in 1919, to Maurice "Hank" Greenberg's time as CEO, until its bailout by the U.S. government in 2008.

Subsequently, he turns toward the regulation of the insurance industry, covering state insurance guarantee funds, the role of the McCarran-Ferguson Act from 1945, as well as the impact of the Dodd-Frank bill on the insurance industry. He devotes special attention to two branches of the insurance industry - life insurance and health insurance - and emphasizes, among other aspects, the consequences of the health care overhaul in the U.S. from 2010. He discusses the example of earthquakes, with insurance in Haiti and catastrophe bonds in Mexico. At the end of the lecture, he critically reflects on the role of the insurance industry in the face of catastrophes.

https://www.youtube.com/watch?v=qfK9rCDCicE

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.

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  • Python for Data Science
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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.