Postmodern portfolio theory : navigating abnormal markets and investor behavior
著者
書誌事項
Postmodern portfolio theory : navigating abnormal markets and investor behavior
（Quantitative perspectives on behavioral economics and finance）
Palgrave Macmillan, c2016
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
This survey of portfolio theory, from its modern origins through more sophisticated, "postmodern" incarnations, evaluates portfolio risk according to the first four moments of any statistical distribution: mean, variance, skewness, and excess kurtosis. In pursuit of financial models that more accurately describe abnormal markets and investor psychology, this book bifurcates beta on either side of mean returns. It then evaluates this traditional risk measure according to its relative volatility and correlation components. After specifying a four-moment capital asset pricing model, this book devotes special attention to measures of market risk in global banking regulation. Despite the deficiencies of modern portfolio theory, contemporary finance continues to rest on mean-variance optimization and the two-moment capital asset pricing model. The term postmodern portfolio theory captures many of the advances in financial learning since the original articulation of modern portfolio theory. A comprehensive approach to financial risk management must address all aspects of portfolio theory, from the beautiful symmetries of modern portfolio theory to the disturbing behavioral insights and the vastly expanded mathematical arsenal of the postmodern critique. Mastery of postmodern portfolio theory's quantitative tools and behavioral insights holds the key to the efficient frontier of risk management.
目次
- Part I - Perpetual Possibility in a World of Speculation: Portfolio Theory in Its Modern and Postmodern Incarnations Chapter 1 - Modern Portfolio Theory 1.1 - Mathematically informed risk management 1.2 - Measures of risk
- the Sharpe ratio 1.3 - Beta 1.4 - The capital asset pricing model 1.5 - The Treynor ratio 1.6 - Alpha 1.7 - The efficient markets hypothesis 1.8 - The efficient frontier Chapter 2 - Postmodern Portfolio Theory 2.1 - A renovation project 2.2 - An orderly walk 2.3 - Roll's critique 2.4 - The echo of future footfalls Part II - Bifurcating Beta in Financial and Behavioral Space Chapter 3 - Seduced by Symmetry, Smarter by Half 3.1 - Splitting the atom of systematic risk 3.2 - The catastrophe of success 3.3 - Reviving beta's dead hand 3.4 - Sinking, fast and slow Chapter 4 -The Full Financial Toolkit of Partial Second Moments 4.1 - A history of downside risk measures 4.2 - Safety first 4.3 - Semivariance, semideviation, and single-sided beta 4.4 - Traditional CAPM specifications of volatility, variance, covariance, correlation, and beta 4.5 - Deriving semideviation and semivariance from upper and lower partial moments Chapter 5 - Sortino, Omega, Kappa: The Algebra of Financial Asymmetry 5.1 - Extracting downside risk measures from lower partial moments 5.2 - The Sortino ratio 5.3 - Comparing the Treynor, Sharpe, and Sortino ratios 5.4 - Pythagorean extensions of second-moment measures: Triangulating deviation about a target not equal to the mean 5.5 - Further Pythagorean extensions: Triangulating semivariance and semideviation 5.6 - Single-sided risk measures in popular financial reporting 5.7 - The trigonometry of semideviation 5.8 - Omega 5.9 - Kappa 5.10 - An overview of single-sided measures of risk based on lower partial moments 5.11 - Noninteger exponents versus ordinary polynomial representations Chapter 6 - Sinking, Fast and Slow: Relative Volatility Versus Correlation Tightening 6.1 - The two behavioral faces of single-sided beta 6.2 - Parameters indicating relative volatility and correlation tightening 6.3 - Relative volatility and the beta quotient 6.4 - The low-volatility anomaly (and Bowman's paradox) 6.5 - Correlation tightening 6.6 - Correlation tightening in emerging markets 6.7 - Isolating and pricing correlation risk 6.8 - Low volatility revisited 6.9 - Low volatility and banking's "curse of quality" 6.10 - Downside risk, upside reward Part III - , : Four Dimensions, Four Moments Chapter 7 - Time-Varying Beta: Autocorrelation and Autoregressive Time Series 7.1 - Finding in motion what was lost in time 7.2 - The conditional capital asset pricing model 7.3 - Conditional beta 7.4 - Conventional time series models 7.5 - Asymmetrical time series models Chapter 8 - Asymmetric Volatility and Volatility Spillovers 8.1 - The origins of asymmetrical volatility
- the leverage effect 8.2 - Volatility feedback 8.3 - Options pricing and implied volatility 8.4 - Asymmetrical volatility and volatility spillover around the world Chapter 9 - A Four-Moment Capital Asset Pricing Model 9.1 - Harbingers of a four-moment capital asset pricing model 9.2 - Four-moment CAPM as a response to the Fama-French-Carhart four-factor model 9.3 - From asymmetric beta to coskewness and cokurtosis 9.4 - Skewness and kurtosis 9.5 - Higher-moment CAPM as a Taylor series expansion 9.6 - Interpreting odd versus even moments 9.7 - Approximating and truncating the Taylor series expansion 9.8 - Profusion and confusion over measures of coskewness and cokurtosis 9.9 - A possible cure for portfolio theory's curse of dimensionality: Relative lower partial moments Chapter 10 - The Practical Implications of a Spatially Bifurcated Four-Moment Capital Asset Pricing Model 10.1 - Four-moment CAPM versus the four-factor model 10.2 - Correlation asymmetry 10.3 - Emerging markets 10.4 - Size, value, and momentum Part IV - Managing Kurtosis: Measures of Market Risk in Global Banking Regulation < Chapter 11 - Going to Extremes: Leptokurtosis as an Epistemic Threat 11.1 - Value-at-risk (VaR) and expected shortfall in global banking regulation 11.2 - Leptokurtosis, fat tails, and non-Gaussian distributions Chapter 12 - Parametric Value-at-Risk (VaR) Analysis 12.1 - The Basel Committee on Bank Supervision and the Basel accords 12.2 - The vulnerability of VaR analysis to model risk 12.3 - Gaussian VaR 12.4 - A simple worked example Chapter 13 - Parametric VaR According to Student's t-Distribution 13.1 - Choosing among non-Gaussian distributions 13.2 - Stable Paretian distributions 13.3 - Student's t-distribution 13.4 - The probability density and cumulative distribution functions of Student's t-distribution 13.5 - Adjusting Student's t-distribution according to observed levels of kurtosis 13.6 - Performing Parametric VaR Analysis with Student's t-distribution Chapter 14 - Comparing Student's t-Distribution with the Logistic Distribution 14.1 - The logistic distribution 14.2 - Equal kurtosis, unequal variance Chapter 15 - Expected Shortfall as a Response to Model Risk 15.1 - Value-at-risk versus expected shortfall 15.2 - The incoherence of VaR 15.3 - Extrapolating expected shortfall from VaR 15.4 - A worked example 15.5 - Formally calculating expected shortfall from VaR under Student's t-distribution 15.6 - Expected shortfall under a logistic model Chapter 16 -Latent Perils: Stressed VaR, Elicitability, and Systemic Risk 16.1 - Additional concerns 16.2 - Stressed VaR 16.3 - Expected shortfall and the elusive ideal of elicitability 16.4 - Systemic risk 16.5 - A dismal forecast Conclusion: Finance as a Romance of Many Moments
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