Advances in portfolio construction and implementation /

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Modern Portfolio Theory explores how risk averse investors construct portfolios in order to optimize market risk against expected returns. The theory quantifies the benefits of diversification. Modern Portfolio Theory provides a broad context for understanding the interactions of systematic risk and...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Satchell, Stephen, 1949-, Scowcroft, Alan
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam ; Oxford : Butterworth-Heinemann, 2003.
Colección:Cambridge elements. Elements in quantitative finance.
Temas:
Portfolio management.
Portfolio management > Mathematical models.
Investments.
Investments
Gestion de portefeuille.
Gestion de portefeuille > Modèles mathématiques.
Investissements.
BUSINESS & ECONOMICS > Investments & Securities > General.
Portfolio management
Portfolio management > Mathematical models
Acceso en línea:Texto completo

MARC

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245 0 0 |a Advances in portfolio construction and implementation /  |c edited by Stephen Satchell, Alan Scowcroft. 
260 |a Amsterdam ;  |a Oxford :  |b Butterworth-Heinemann,  |c 2003. 
300 |a 1 online resource (xvi, 365 pages). 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a data file  |2 rda 
490 1 |a Butterworth-Heinemann finance 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
505 0 |a Front Cover; Advances in Portfolio Construction and Implementation; Copyright Page; Contents; List of Contributors; Introduction; Chapter 1. A review of portfolio planning: models and systems; 1.1 Introduction and Overview; 1.2 Alternative Computational Models; 1.3 Symmetric and Asymmetric Measures of Risk; 1.4 Computational Models in Practice; 1.5 Preparation of Data: Financial Data Marts; 1.6 Solution Methods; 1.7 Computational Experience; 1.8 Discussions and Conclusions; 1.9 Appendix 1: Piecewise Linear Approximation of the Quadratic Form. 
505 8 |a 1.10 Appendix 2: Comparative Computational Views of the Alternative ModelsReferences; Web References; Acknowledgements; Chapter 2. Generalized mean-variance analysis and robust portfolio diversification; 2.1 Introduction; 2.2 Generalized Mean-Variance Analysis; 2.3 The State Preference Theory Approach to Portfolio Construction; 2.4 Implementation and Simulation; 2.5 Conclusions and Suggested Further Work; References; Chapter 3. Portfolio construction from mandate to stock weight: a practitioner's perspective; 3.1 Introduction; 3.2 Allocating Tracking Error for Multiple Portfolio Funds. 
505 8 |a 3.3 Tracking Errors for Arbitrary Portfolios3.4 Active CAPM, or How Far Should a Bet be Taken?; 3.5 Implementing Ideas in Real Stock Portfolios; 3.6 Conclusions; References; Chapter 4. Enhanced indexation; 4.1 Introduction; 4.2 Constructing a Consistent View; 4.3 Enhanced Indexing; 4.4 An Illustrative Example: Top-down or Bottom-up?; 4.5 Conclusions; 4.6 Appendix 1: Derivation of the Theil-Goldberger Mixed Estimator; 4.7 Appendix 2: Optimization; References; Notes; Chapter 5. Portfolio management under taxes; 5.1 Introduction; 5.2 Do Taxes Really Matter to Investors and Managers? 
505 8 |a 5.3 The Core Problems5.4 The State of the Art; 5.5 The Multi-Period Aspect; 5.6 Loss Harvesting; 5.7 After-Tax Benchmarks; 5.8 Conclusions; References; Chapter 6. Using genetic algorithms to construct portfolios; 6.1 Limitations of Traditional Mean-Variance Portfolio Optimization; 6.2 Selecting a Method to Limit the Number of Securities in the Final Portfolio; 6.3 Practical Construction of a Genetic Algorithm-Based Optimizer; 6.4 Performance of Genetic Algorithm; 6.5 Conclusions; References; Chapter 7. Near-uniformly distributed, stochastically generated portfolios. 
505 8 |a 7.1 Introduction -- A Tractable N-Dimensional Experimental Control7.2 Applications; 7.3 Dynamic Constraints; 7.4 Results from the Dynamic Constraints Algorithm; 7.5 Problems and Limitations with Dynamic Constraints Algorithm; 7.6 Improvements to the Distribution; 7.7 Results of the Dynamic Constraints with Local Density Control; 7.8 Conclusions; 7.9 Further Work; 7.10 Appendix 1: Review of Holding Distribution in Low Dimensions with Minimal Constraints; 7.11 Appendix 2: Probability Distribution of Holding Weight in Monte Carlo Portfolios in N Dimensions with Minimal Constraints. 
520 |a Modern Portfolio Theory explores how risk averse investors construct portfolios in order to optimize market risk against expected returns. The theory quantifies the benefits of diversification. Modern Portfolio Theory provides a broad context for understanding the interactions of systematic risk and reward. It has profoundly shaped how institutional portfolios are managed, and has motivated the use of passive investment management techniques, and the mathematics of MPT is used extensively in financial risk management. Advances in Portfolio Construction and Implementation o. 
546 |a English. 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
650 0 |a Portfolio management. 
650 0 |a Portfolio management  |x Mathematical models. 
650 0 |a Investments. 
650 2 |a Investments 
650 6 |a Gestion de portefeuille. 
650 6 |a Gestion de portefeuille  |x Modèles mathématiques. 
650 6 |a Investissements. 
650 7 |a BUSINESS & ECONOMICS  |x Investments & Securities  |x General.  |2 bisacsh 
650 7 |a Investments  |2 fast 
650 7 |a Portfolio management  |2 fast 
650 7 |a Portfolio management  |x Mathematical models  |2 fast 
700 1 |a Satchell, Stephen,  |d 1949- 
700 1 |a Scowcroft, Alan. 
776 0 8 |i Print version:  |t Advances in portfolio construction and implementation.  |d Amsterdam ; Oxford : Butterworth-Heinemann, 2003  |w (DLC) 2002036111 
830 0 |a Cambridge elements.  |p Elements in quantitative finance. 
856 4 0 |u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=104696  |z Texto completo 
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938 |a EBSCOhost  |b EBSC  |n 104696 
938 |a YBP Library Services  |b YANK  |n 2348335 
994 |a 92  |b IZTAP 

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