Lecture 7 - Efficient Markets

Initially, Professor Shiller looks back at David Swensen's guest lecture, in particular with respect to the Sharpe ratio as a performance measure for investment strategies. He emphasizes the empirical difficulty to measure the standard deviation, specifically for illiquid asset classes, and elaborates on investment strategies that manipulate the Sharpe ratio.
Subsequently, he focuses on the Efficient Markets Hypothesis. This theory states that markets efficiently incorporate all public information, which consequently renders beating the market impossible. For example, technical analysis fails to provide powerful, short-run profit opportunities.

A consequence of the Efficient Markets Hypothesis is that stock prices follow a Random Walk, as innovations to the stock price must be solely attributable to news. Professor Shiller contrasts the behavior of a Random Walk with that of a First-Order Autoregressive Process, and concludes that the latter statistical process matches the reality of the stock market more closely. This conclusion, combined with the evidence that investment managers like David Swensen are capable of consistently outperforming the market leads Professor Shiller to the conclusion that the Efficient Markets Hypothesis is a half-truth.

Additional Resources:

Multiple-Choice Quiz (with answer key) [PDF]

Lehrer, "The Truth Wears Off: Is There Something Wrong with the Scientific Method?" The New Yorker

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 $39 (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.