The Capital Market Line

On a graph, the Capital Allocation line (CAL)  starts at the risk-free return and runs tangent to the minimum variance frontier for any group of risk assets.

On a graph, the Capital Market Line (CML) starts from the risk-free return on the y-int and runs tangent to the efficient frontier at the market portfolio.

Market Portfolio is portfolio representing the weighted value of all investible assets.

The idea is that all investors all investors agree to common expectations for all assets, i.e., expected returns, standard deviations and correlations. When there is only one sent of expectations there will be only one capital allocation line, called the Capital Market Line.

Since all the investors have the same expectations, they all are agreeing on similar composition of optimal risky portfolio, which is called the market portfolio.

The line equation for the CML is the same as the CAL and the slope coefficient is the Sharpe Ratio formula. CML is actually a special case of CAL.

Note that there is only one CML common for all investors, while there are unlimited CALs unique for each investor.

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.