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What is Modern Portfolio Theory
Modern portfolio theory (MPT), or mean-variance analysis, is a mathematical framework for assembling a portfolio of assets such that the expected return is maximized for a given level of risk. It is a formalization and extension of diversification in investing, the idea that owning different kinds of financial assets is less risky than owning only one type. Its key insight is that an asset's risk and return should not be assessed by itself, but by how it contributes to a portfolio's overall risk and return. The variance of return is used as a measure of risk, because it is tractable when assets are combined into portfolios. Often, the historical variance and covariance of returns is used as a proxy for the forward-looking versions of these quantities, but other, more sophisticated methods are available.
How you will benefit
(I) Insights, and validations about the following topics:
Chapter 1: Modern portfolio theory
Chapter 2: Standard deviation
Chapter 3: Variance
Chapter 4: Multivariate normal distribution
Chapter 5: Correlation
Chapter 6: Capital asset pricing model
Chapter 7: Covariance matrix
Chapter 8: Pearson correlation coefficient
Chapter 9: Propagation of uncertainty
Chapter 10: Beta (finance)
Chapter 11: Tracking error
Chapter 12: Diversification (finance)
Chapter 13: Merton's portfolio problem
Chapter 14: Single-index model
Chapter 15: Post-modern portfolio theory
Chapter 16: Risk measure
Chapter 17: Treynor-Black model
Chapter 18: Goal-based investing
Chapter 19: Two-moment decision model
Chapter 20: Mutual fund separation theorem
Chapter 21: Financial correlation
(II) Answering the public top questions about modern portfolio theory.
(III) Real world examples for the usage of modern portfolio theory in many fields.
Who this book is for
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Modern Portfolio Theory.
Modern portfolio theory (MPT), or mean-variance analysis, is a mathematical framework for assembling a portfolio of assets such that the expected return is maximized for a given level of risk. It is a formalization and extension of diversification in investing, the idea that owning different kinds of financial assets is less risky than owning only one type. Its key insight is that an asset's risk and return should not be assessed by itself, but by how it contributes to a portfolio's overall risk and return. The variance of return is used as a measure of risk, because it is tractable when assets are combined into portfolios. Often, the historical variance and covariance of returns is used as a proxy for the forward-looking versions of these quantities, but other, more sophisticated methods are available.
How you will benefit
(I) Insights, and validations about the following topics:
Chapter 1: Modern portfolio theory
Chapter 2: Standard deviation
Chapter 3: Variance
Chapter 4: Multivariate normal distribution
Chapter 5: Correlation
Chapter 6: Capital asset pricing model
Chapter 7: Covariance matrix
Chapter 8: Pearson correlation coefficient
Chapter 9: Propagation of uncertainty
Chapter 10: Beta (finance)
Chapter 11: Tracking error
Chapter 12: Diversification (finance)
Chapter 13: Merton's portfolio problem
Chapter 14: Single-index model
Chapter 15: Post-modern portfolio theory
Chapter 16: Risk measure
Chapter 17: Treynor-Black model
Chapter 18: Goal-based investing
Chapter 19: Two-moment decision model
Chapter 20: Mutual fund separation theorem
Chapter 21: Financial correlation
(II) Answering the public top questions about modern portfolio theory.
(III) Real world examples for the usage of modern portfolio theory in many fields.
Who this book is for
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Modern Portfolio Theory.
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