Postmodern Portfolio Theory 2016

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"/p> 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 - TAU sigmasigmaepsilonrhoalpha, TAU sigmasigmaepsilonrhoalpha : 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"/p> 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