Portfolio Optimization with Stochastic Dominance Constraints

Portfolio Optimization with Stochastic Dominance Constraints PDF Author: Darinka Dentcheva
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Portfolio Optimization with Stochastic Dominance Constraints

Portfolio Optimization with Stochastic Dominance Constraints PDF Author: Darinka Dentcheva
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Stochastic dominance in portfolio analysis and asset pricing

Stochastic dominance in portfolio analysis and asset pricing PDF Author: Andrey M. Lizyayev
Publisher: Rozenberg Publishers
ISBN: 9036101875
Category :
Languages : en
Pages : 136

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Stochastic Optimization Models In Finance (2006 Edition)

Stochastic Optimization Models In Finance (2006 Edition) PDF Author: William T Ziemba
Publisher: World Scientific
ISBN: 9814478075
Category : Business & Economics
Languages : en
Pages : 756

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Book Description
A reprint of one of the classic volumes on portfolio theory and investment, this book has been used by the leading professors at universities such as Stanford, Berkeley, and Carnegie-Mellon. It contains five parts, each with a review of the literature and about 150 pages of computational and review exercises and further in-depth, challenging problems.Frequently referenced and highly usable, the material remains as fresh and relevant for a portfolio theory course as ever.

Portfolio Optimization with DARA Stochastic Dominance Constraints

Portfolio Optimization with DARA Stochastic Dominance Constraints PDF Author: Milos Kopa
Publisher:
ISBN:
Category :
Languages : en
Pages : 43

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Book Description
An optimization method is developed for constructing investment portfolios which stochastically dominate a given benchmark for all decreasing absolute risk-averse investors, using Quadratic Programming. The method is applied to standard data sets of historical returns of equity price reversal and momentum portfolios. The proposed optimization method improves upon the performance of Mean-Variance optimization by tens to hundreds of basis points per annum, for low to medium risk levels. The improvements critically depend on imposing the complex condition of Decreasing Absolute Risk Aversion in addition to the simpler conditions of global risk aversion and decreasing risk aversion.

Modern Portfolio Optimization with NuOPT™, S-PLUS®, and S+Bayes™

Modern Portfolio Optimization with NuOPT™, S-PLUS®, and S+Bayes™ PDF Author: Bernd Scherer
Publisher: Springer Science & Business Media
ISBN: 0387210164
Category : Business & Economics
Languages : en
Pages : 422

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Book Description
Portfolio optimization and construction methodologies have become an critical ingredient of asset and fund management, while at same time portfolio risk assesment has become an essential ingredient in risk management.

Study of Portfolio Optimization Considering the Third-Order Stochastic Dominance and Skewness

Study of Portfolio Optimization Considering the Third-Order Stochastic Dominance and Skewness PDF Author: 陳證安
Publisher:
ISBN:
Category :
Languages : en
Pages : 174

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Optimal Portfolios: Stochastic Models For Optimal Investment And Risk Management In Continuous Time

Optimal Portfolios: Stochastic Models For Optimal Investment And Risk Management In Continuous Time PDF Author: Ralf Korn
Publisher: World Scientific
ISBN: 9814497126
Category : Business & Economics
Languages : en
Pages : 352

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Book Description
The focus of the book is the construction of optimal investment strategies in a security market model where the prices follow diffusion processes. It begins by presenting the complete Black-Scholes type model and then moves on to incomplete models and models including constraints and transaction costs. The models and methods presented will include the stochastic control method of Merton, the martingale method of Cox-Huang and Karatzas et al., the log optimal method of Cover and Jamshidian, the value-preserving model of Hellwig etc.Stress is laid on rigorous mathematical presentation and clear economic interpretations while technicalities are kept to the minimum. The underlying mathematical concepts will be provided. No a priori knowledge of stochastic calculus, stochastic control or partial differential equations is necessary (however some knowledge in stochastics and calculus is needed).

Stochastic Portfolio Theory

Stochastic Portfolio Theory PDF Author: E. Robert Fernholz
Publisher: Springer Science & Business Media
ISBN: 1475736991
Category : Business & Economics
Languages : en
Pages : 190

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Book Description
Stochastic portfolio theory is a mathematical methodology for constructing stock portfolios and for analyzing the effects induced on the behavior of these portfolios by changes in the distribution of capital in the market. Stochastic portfolio theory has both theoretical and practical applications: as a theoretical tool it can be used to construct examples of theoretical portfolios with specified characteristics and to determine the distributional component of portfolio return. This book is an introduction to stochastic portfolio theory for investment professionals and for students of mathematical finance. Each chapter includes a number of problems of varying levels of difficulty and a brief summary of the principal results of the chapter, without proofs.

Advances in the use of stochastic dominance in asset pricing

Advances in the use of stochastic dominance in asset pricing PDF Author: Philippe Johannes Petrus Marie Versijp
Publisher: Rozenberg Publishers
ISBN: 9051709358
Category :
Languages : en
Pages : 128

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Book Description


Linear and Mixed Integer Programming for Portfolio Optimization

Linear and Mixed Integer Programming for Portfolio Optimization PDF Author: Renata Mansini
Publisher: Springer
ISBN: 3319184822
Category : Business & Economics
Languages : en
Pages : 131

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Book Description
This book presents solutions to the general problem of single period portfolio optimization. It introduces different linear models, arising from different performance measures, and the mixed integer linear models resulting from the introduction of real features. Other linear models, such as models for portfolio rebalancing and index tracking, are also covered. The book discusses computational issues and provides a theoretical framework, including the concepts of risk-averse preferences, stochastic dominance and coherent risk measures. The material is presented in a style that requires no background in finance or in portfolio optimization; some experience in linear and mixed integer models, however, is required. The book is thoroughly didactic, supplementing the concepts with comments and illustrative examples.