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Postmodern Portfolio Theory

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Cover of 'Postmodern Portfolio Theory'

Table of Contents

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    Book Overview
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    Chapter 1 Finance as a Pattern of Timeless Moments
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    Chapter 2 Modern Portfolio Theory
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    Chapter 3 Postmodern Portfolio Theory
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    Chapter 4 Seduced by Symmetry, Smarter by Half
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    Chapter 5 The Full Financial Toolkit of Partial Second Moments
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    Chapter 6 Sortino, Omega, Kappa: The Algebra of Financial Asymmetry
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    Chapter 7 Sinking, Fast and Slow: Relative Volatility Versus Correlation Tightening
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    Chapter 8 Time-Varying Beta: Autocorrelation and Autoregressive Time Series
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    Chapter 9 Asymmetric Volatility and Volatility Spillovers
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    Chapter 10 A Four-Moment Capital Asset Pricing Model
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    Chapter 11 The Practical Implications of a Spatially Bifurcated Four-Moment Capital Asset Pricing Model
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    Chapter 12 Going to Extremes: Leptokurtosis as an Epistemic Threat
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    Chapter 13 Parametric VaR Analysis
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    Chapter 14 Parametric VaR According to Student’s t -Distribution
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    Chapter 15 Comparing Student’s t -Distribution with the Logistic Distribution
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    Chapter 16 Expected Shortfall as a Response to Model Risk
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    Chapter 17 Latent Perils: Stressed VaR, Elicitability, and Systemic Effects
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    Chapter 18 Finance as a Romance of Many Moments and Plural Views
Attention for Chapter 14: Parametric VaR According to Student’s t -Distribution
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Chapter title
Parametric VaR According to Student’s t -Distribution
Chapter number 14
Book title
Postmodern Portfolio Theory
Published by
Palgrave Macmillan, New York, January 2016
DOI 10.1057/978-1-137-54464-3_14
Book ISBNs
978-1-137-54463-6, 978-1-137-54464-3
Authors

James Ming Chen

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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