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Multi-moment Asset Allocation and Pricing Models (The Wiley Finance Series)
 
 
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Multi-moment Asset Allocation and Pricing Models (The Wiley Finance Series) [Hardcover]

Emmanuel Jurczenko (Editor), Bertrand Maillet (Editor), Mark Rubinstein (Foreword)

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Book Description

0470034157 978-0470034156 December 11, 2006 1
While mainstream financial theories and applications assume that asset returns are normally distributed and individual preferences are quadratic, the overwhelming empirical evidence shows otherwise. Indeed, most of the asset returns exhibit “fat-tails” distributions and investors exhibit asymmetric preferences. These empirical findings lead to the development of a new area of research dedicated to the introduction of higher order moments in portfolio theory and asset pricing models.

Multi-moment asset pricing is a revolutionary new way of modeling time series in finance which allows various degrees of long-term memory to be generated. It allows risk and prices of risk to vary through time enabling the accurate valuation of long-lived assets.

This book presents the state-of-the art in multi-moment asset allocation and pricing models and provides many new developments in a single volume, collecting in a unified framework theoretical results and applications previously scattered throughout the financial literature. The topics covered in this comprehensive volume include: four-moment individual risk preferences, mathematics of the multi-moment efficient frontier, coherent asymmetric risks measures, hedge funds asset allocation under higher moments, time-varying specifications of (co)moments and multi-moment asset pricing models with homogeneous and heterogeneous agents.

Written by leading academics, Multi-moment Asset Allocation and Pricing Models offers a unique opportunity to explore the latest findings in this new field of research.


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Editorial Reviews

From the Inside Flap

While mainstream financial theories and applications assume that asset returns are normally distributed and individual preferences are quadratic, the overwhelming empirical evidence shows otherwise. Indeed, most of the asset returns exhibit “fat-tails” distributions and investors exhibit asymmetric preferences. These empirical findings lead to the development of a new area of research dedicated to the introduction of higher order moments in portfolio theory and asset pricing models.

This book presents the state-of-the art in multi-moment asset allocation and pricing models and provides many new developments in a single volume, collecting in a unified framework theoretical results and applications previously scattered throughout the financial literature. The topics covered in this comprehensive volume include: four-moment individual risk preferences, mathematics of the multi-moment efficient frontier, coherent asymmetric risks measures, hedge funds asset allocation under higher moments, time-varying specifications of (co)moments and multi-moment asset pricing models with homogeneous and heterogeneous agents.

Written by leading academics, Multi-moment Asset Allocation and Pricing Modelsoffers a unique opportunity to explore the latest findings in this new field of research.

From the Back Cover

When I developed the first multi-moment CAPM as the lead paper in my dissertation in 1970, I had high hopes that this would lead to significant improvements in asset pricing. I felt intuitively that at least the skewness and kurtosis of portfolio returns would matter to investors. Skewness preference captures asymmetric concern over downside outcomes and kurtosis captures the implications of extreme rare events, that are more numerous than indicated by normal distributions. Unfortunately, very little interest was shown in the multi-moment model for the next 30 years. Indeed, in prominent reviews of the CAPM, the generalization to many moments was rarely even mentioned. Then, the apparent empirical failure of the two-moment CAPM and the publication of several recent articles that take higher-order moments seriously, and now even a full book just devoted to the subject, have given new life to these ideas.” —Mark Rubinstein, Paul Stephens Professor of Applied Investment Analysis, UC Berkeley, USA

In a less well-known part of his path-breaking 1952 article on ‘Portfolio Selection’, Harry Markowitz details the conditions whereby mean-variance efficient portfolios will not be optimal. Markowitz argues that if investors have utility which depends on not only mean and variance but also skewness, then this could lead to a different set of optimal portfolios. This insight lay fallow for more than 20 years. It was revived in the important work of Mark Rubinstein in 1973. Since the late 1990s, we have seen an explosion of research on higher moments. People are beginning to think of the efficient frontier – as the efficient surface (incorporating skewness and other higher moments). This interest is sparked by five factors. First, it is obvious that people have a preference for positively skewed outcomes rather than negatively skewed returns (holding mean and variance constant). Second, most asset returns are non-normal. Third, it is widely acknowledged that two-moment CAPM has trouble fitting the data. Fourth, there is a large growth in a style of investing, sometimes referred to as alternatives, whose expected returns have option-like, non-normal features. Finally, computing power has advanced to such a degree that we can feasibly tackle the difficult problem of solving for optimal portfolios in the presence of higher moments. The time is right for a book on higher moments in asset pricing - and this is the right book.” —Campbell R. Harvey, J. Paul Sticht Professor of International Business, Duke University, USA

Plenty of evidence has emerged in the financial literature that the distributional assumptions underlying mean-variance analysis do not hold. Returns on many individual assets as well as returns on actively managed mutual funds have been found to be skewed and fat-tailed and are affected by occasional outliers. Unless investors have quadratic preferences, in equilibrium an asset's skew and kurtosis should generally be priced. The focus of the traditional CAPM on the first two moments was made out of analytical convenience, but we now have better tools to go beyond this analysis. The time is right for a book on the multi-moment CAPM and its related topics.” —Allan Timmermann, Professor of Economics, University of California at San Diego, USA


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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
cubic market model, maximum skewness portfolio, risk premia using higher moments, seventeen assets, expected gross rate, shortage function, monthly net asset values, skewed asset returns, centred moments, market portfolio return, pth order moments, risky asset returns, asset pricing relation, portfolio whose return, decreasing absolute prudence, asset return distributions, portfolio return distribution, same dependence structure, systematic risk measures, conditional skewness, portfolio choice theory, optimisation programme, asset pricing tests, portfolio moments, increasing relative risk aversion
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Journal of Finance, Journal of Business, John Wiley, Journal of Financial Economics, Management Science, Journal of Empirical Finance, New York, Review of Financial Studies, Journal of Econometrics, Journal of Economic Theory, Journal of Portfolio Management, Quantitative Finance, American Economic Review, Princeton University Press, Risk Management, Journal of Political Economy, University of Munich, Arbitrage Pricing Theory, Asset Pricing Model Comparison, Eric Jondeau, Federal Reserve Bank of St Louis, Multivariate Skew-Student Distribution, Regime Switching, Duke University, Finance Letters
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