Lecture 10 - Real Estate Finance

Real estate finance is so important that it has a very long and complex history. Describing the history of mortgage financing, Professor Shiller highlights the historical development of well-institutionalized property rights for mortgage contracts.

Subsequently, he focuses on modern financial institutions for commercial real estate, elaborating on Direct Participation Programs and Real Estate Investment Trusts as means for its financing. The distinction between short-term, balloon-payment mortgages before the Great Depression and long-term, amortizing mortgages thereafter shapes the discussion of residential real estate.

His discussion of mortgage securitization and government support of mortgage markets centers around Fannie Mae and Freddie Mac, from their inception in 1938 and 1970, respectively, to the U.S. government's decision to put them into federal conservatorship in 2008. Finally, Professor Shiller covers collateralized mortgage obligations (CMOs) and elaborates on moral hazard in the mortgage origination process.

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 includes PDFs, explanations, instructions, data files, and R code for all examples.

Get the Bundle for $29 (Regular $57)
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

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.