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By Frank J. Fabozzi, Sergio M. Focardi, Petter N. Kolm, Dessislava A. Pachamanova

Compliment for powerful Portfolio Optimization and Management

"In the part century due to the fact that Harry Markowitz brought his dependent concept for choosing portfolios, traders and students have prolonged and subtle its software to a variety of real-world difficulties, culminating within the contents of this masterful ebook. Fabozzi, Kolm, Pachamanova, and Focardi deserve excessive compliment for generating a technically rigorous but remarkably obtainable consultant to the most recent advances in portfolio construction."
--Mark Kritzman, President and CEO, Windham Capital administration, LLC

"The subject of sturdy optimization (RO) has turn into 'hot' during the last numerous years, particularly in real-world monetary purposes. This curiosity has been sparked, partly, via practitioners who carried out classical portfolio types for asset allocation with no contemplating estimation and version robustness part of their total allocation technique, and skilled negative functionality. someone drawn to those advancements should personal a duplicate of this publication. The authors disguise the new advancements of the RO sector in an intuitive, easy-to-read demeanour, supply a number of examples, and speak about functional issues. I hugely suggest this booklet to finance execs and scholars alike."
--John M. Mulvey, Professor of Operations learn and fiscal Engineering, Princeton collage

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An Empirical Exploration of Idiosyncratic Risk,” Journal of Finance 56, no. 1 (February 2001), pp. 1–43. 6 Burton G. ” Proceedings of the AIMR seminar “The Future of Equity Portfolio Construction,” March 2002, pp. 26–27. 7 Raman Vardharaj, Frank J. Fabozzi, and Frank J. Jones, “Determinants of Tracking Error for Equity Portfolios,” Journal of Investing 13, no. 2 (Summer 2004), pp. 37–47. ch2-Mean-Var Page 21 Tuesday, March 6, 2007 12:17 PM Mean-Variance Analysis and Modern Portfolio Theory 21 a vast number of the innovations surrounding finance have either been in the application of the concept of diversification, or the introduction of new methods for obtaining improved estimates of the variances and covariances, thereby allowing for a more precise measure of diversification and consequently, for a more precise measure of risk.

In this chapter, we begin with a general discussion of the benefits of diversification before we introduce the classical mean-variance framework. We derive the mean-variance portfolio for equality constraints and then illustrate some of its basic properties through practical examples. In particular, we show how the shape of the so-called efficient frontier changes with the addition of other assets (risky as well as risk-free) and with the introduction of short-selling constraints. In the presence of only risky assets, the mean-variance efficient frontier has a parabolic shape.

Mueller, Michel M. Dacorogna, and Olivier V. Pictet, “Heavy Tails in High-Frequency Financial Data, in Robert J. Adler, Raya E. Feldman, and Murad S. ), A Practical Guide to Heavy Tails (Boston, MA: Birkhaeuser, 1998), pp. 55–77. 19 For recent empirical evidence on the distribution of asset returns and portfolio selection when distributions are nonnormal, see Svetlozar T. Rachev, and Stefan Mittnik, Stable Paretian Models in Finance (Chichester: John Wiley & Sons, 2000); and Svetlozar T. ), Handbook of Heavy Tailed Distributions in Finance (New York: Elsevier/North Holland, 2001).

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