- CFA Level 2: Portfolio Management – Introduction
- Mean-Variance Analysis Assumptions
- Expected Return and Variance for a Two Asset Portfolio
- The Minimum Variance Frontier & Efficient Frontier
- Diversification Benefits
- The Capital Allocation Line – Introducing the Risk-free Asset
- The Capital Market Line
- CAPM & the SML
- Adding an Asset to a Portfolio – Improving the Minimum Variance Frontier
- The Market Model for a Security’s Returns
- Adjusted and Unadjusted Beta
- Multifactor Models
- Arbitrage Portfolio Theory (APT) – A Multifactor Macroeconomic Model
- Risk Factors and Tracking Portfolios
- Markowitz, MPT, and Market Efficiency
- International Capital Market Integration
- Domestic CAPM and Extended CAPM
- Changes in Real Exchange Rates
- International CAPM (ICAPM) - Beyond Extended CAPM
- Measuring Currency Exposure
- Company Stock Value Responses to Changes in Real Exchange Rates
- ICAPM vs. Domestic CAPM
- The J-Curve – Impact of Exchange Rate Changes on National Economies
- Moving Exchange Rates and Equity Markets
- Impacts of Market Segmentation on ICAPM
- Justifying Active Portfolio Management
- The Treynor-Black Model
- Portfolio Management Process
- The Investor Policy Statement
The Minimum Variance Frontier & Efficient Frontier
Two asset classes (stocks and bonds for example) can be combined with varying proportions to create an infinite number of portfolios.
An investor can calculate the expected returns and variances of a two asset portfolio and plotting these on the Y (returns) and X (variances) axis of a graph.
Global Minimum Variance Portfolio: The portfolio with the lowest risk/variance on the efficient frontier.
Efficient Frontier: Starting with the global minimum variance portfolio and extending to the portfolio of 100% stocks, the efficient frontier is the series of optimal portfolios that can be constructed from two assets, each offering the highest returns for a given amount of risk.
Note that in a two asset case, a portfolio of 100% bonds will fall on the minimum variance frontier, but be excluded from the efficient frontier as applying some small portion of stocks to the portfolio will offer higher returns and a lower level of risk through the benefits of diversification.
Multi Asset Portfolios (three or more asset classes)
- In a two asset class portfolio, all of the portfolio combinations will lie on the minimum variance frontier.
- For three or more asset classes, many portfolio combinations will be inefficient and fall inside the frontier.
- For a three asset class portfolio, the highest and lowest possible returning portfolios will lie on the minimum variance frontier.
No portfolios can be above the efficient frontier.
As an investment rule, only portfolios on the efficient frontier should be considered.
Instability of the Minimum Variance Frontier and Portfolio Implications
When calculating portfolios on the minimum variance frontier, it must be recognized that the output values are highly sensitive to the data input values for returns, variances, and correlations. Small changes to these values can create large shifts in the frontier.
Data Input Challenges
- Sampling techniques to obtain return, variance, and correlation data can fall victim to sampling error.
- The values of these inputs change over time.
The optimal portfolio often requires taking short positions, which is not practical or not allowable for many portfolio managers.
Regularly changing estimates to inputs can indicate a need to rebalance frequently, which is expensive.
Data Science in Finance: 9-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)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.