Autore	Lindquist W. Brent
Pubbl/distr/stampa	Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica	1 online resource (268 pages)
Disciplina	658.155
Collana	Dynamic modeling and econometrics in economics and finance
Soggetto topico	Financial risk management Portfolio management Portfolio management - Mathematical models
ISBN	3-031-15286-7
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Intro -- Foreword -- About This Book -- Contents -- Abbreviations -- Chapter 1: The Real Estate Investment Market: The Current State and Why Advances Are Needed -- References -- Chapter 2: The Data -- 2.1 REIT Asset Descriptions -- 2.1.1 Domestic REITs -- 2.1.2 International REITs -- 2.2 Real Estate Stock Descriptions -- 2.3 Benchmarks -- 2.3.1 Indices -- 2.3.2 Exchange Traded Funds -- 2.3.3 Mutual Funds -- 2.4 Additional Assets and Indices -- 2.5 Data Observations -- References -- Chapter 3: Modern Portfolio Theory -- 3.1 Return Time Series -- 3.2 MPT-Based Portfolios -- 3.2.1 Markowitz Mean-Variance Portfolio -- 3.2.2 Capital Market Line and the Markowitz Mean-Variance Tangent Portfolio -- 3.2.3 CVaR-Minimizing Portfolios -- 3.2.4 Capital Market Line and the CVaRα Tangent Portfolio -- 3.2.5 Criticisms of Mean-Variance Optimization -- 3.3 Black-Litterman Model -- 3.4 Historical Optimization -- References -- Chapter 4: Historical Portfolio Optimization: Domestic REITs -- 4.1 Basic Strategies, Price, and Return Performance -- 4.1.1 Long-Only Strategy -- 4.1.2 Jacobs et al. Long-Short Strategy -- 4.1.3 Lo-Patel Long-Short Strategy -- 4.1.4 Long-Short Momentum Strategy -- 4.2 Performance Under Turnover Constraints -- 4.3 Performance-Risk Measures -- 4.4 Observations -- References -- Chapter 5: Diversification with International REITs -- 5.1 International Portfolio Performance -- 5.1.1 Long-Only International Portfolios -- 5.1.2 Jacobs et al. Long-Short International Portfolios -- 5.1.3 Lo-Patel Long-Short International Portfolios -- 5.2 Global Portfolio Performance -- 5.2.1 Long-Only Global Portfolios -- 5.2.2 Jacobs et al. Long-Short Global Portfolios -- References -- Chapter 6: Black-Litterman Optimization Results -- 6.1 Domestic Portfolios -- 6.2 Global Portfolios -- Chapter 7: Dynamic Portfolio Optimization: Beyond MPT. 7.1 Dynamic Optimization -- 7.1.1 ARMA(1,1)-GARCH(1,1) with Student´s t-Distribution -- 7.1.2 Multivariate t-Distribution and t-Copulas -- 7.1.3 Generation of Dynamic Returns -- 7.1.4 Combining the Dynamic Approach with Black-Litterman Optimization -- 7.2 Portfolio Optimization Using Dynamic Returns -- 7.2.1 Dynamic Long-Only Portfolios -- 7.2.2 Dynamic Jacobs et al. Long-Short Portfolios -- 7.2.3 Dynamic Lo-Patel Long-Short Portfolios -- 7.3 Dynamic Optimization with the Black-Litterman Model -- References -- Chapter 8: Backtesting -- 8.1 VaR Tests -- 8.1.1 Binomial Test -- 8.1.2 Traffic Light Test -- 8.1.3 Kupiec´s Tests -- 8.1.4 Christoffersen´s Tests -- 8.1.5 Haas´s Tests -- 8.2 Backtest Results -- 8.2.1 Historical Optimization -- 8.2.2 Dynamic Optimizations -- References -- Chapter 9: Diversification with Real Estate Stocks -- Chapter 10: Risk Information and Management -- 10.1 Early Warning Systems -- 10.1.1 Chow Test for a Structural Break -- 10.1.2 Early Warning Based on Tail-Loss Ratio -- 10.1.3 Early Warning Based on Mahalanobis Distance -- 10.1.3.1 Copulas -- 10.1.3.2 Mahalanobis Distance -- 10.2 Asset Weighting -- 10.3 Risk Budgets: Incremental and Component Risk -- 10.3.1 Incremental, Marginal, and Component VaR -- 10.3.2 Computing VaR, IVaR, MVaR, and ciVaR -- 10.3.3 Portfolio Results -- 10.4 Factor Analysis -- References -- Chapter 11: Optimization with Performance-Attribution Constraints -- 11.1 Performance-Attribute Constraints -- 11.2 Application to Domestic REIT Portfolio -- References -- Chapter 12: Option Pricing -- 12.1 Double Subordinated Pricing Models -- 12.2 Option Pricing Under the Double Subordinated IG Model -- 12.3 Empirical Example -- 12.3.1 Choice of a and vmax -- 12.3.2 Option Price and Implied Volatility Surfaces -- 12.4 Volatility Measures -- Appendix 1 -- Appendix 2 -- References. Chapter 13: Inclusion of ESG Ratings in Optimization -- 13.1 REIT ESG Data -- 13.2 ESG-Valued Returns -- 13.3 ESG-Valued Optimization -- 13.4 The ESG Efficient Frontier -- 13.5 ESG-Valued Tangent Portfolios -- 13.5.1 Tangent Portfolio Performance over Time -- 13.6 ESG-Valued Reward-Risk Measures -- References -- Chapter 14: Inclusion of ESG Ratings in Option Pricing -- 14.1 Discrete Return Binomial Pricing Model -- 14.2 ESG-Valued Return Binomial Pricing Model -- 14.3 ESG-Valued Option Pricing Using a REIT Portfolio as the Underlying -- References.
Record Nr.	UNINA-9910624311803321

Autore	Rachev S. T (Svetlozar Todorov)
Pubbl/distr/stampa	Hoboken, N.J., : Wiley
Descrizione fisica	1 online resource (39 p.)
Disciplina	332
Altri autori (Persone)	StoyanovStoyan V FabozziFrank J
Collana	The Frank J. Fabozzi series
Soggetto topico	Stochastic processes Mathematical optimization Risk assessment - Mathematical models Portfolio management - Mathematical models
Soggetto genere / forma	Electronic books.
ISBN	1-281-21730-1 0-470-25360-6 9786611217303 1-283-27295-4 9786613272959 1-118-08614-7
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization; Contents; Preface; Acknowledgments; About the Authors; Chapter 1 Concepts of Probability; 1.1 INTRODUCTION; 1.2 BASIC CONCEPTS; 1.3 DISCRETE PROBABILITY DISTRIBUTIONS; 1.4 CONTINUOUS PROBABILITY DISTRIBUTIONS; 1.5 STATISTICAL MOMENTS AND QUANTILES; 1.6 JOINT PROBABILITY DISTRIBUTIONS; 1.7 PROBABILISTIC INEQUALITIES; 1.8 SUMMARY; BIBLIOGRAPHY; Chapter 2 Optimization; 2.1 INTRODUCTION; 2.2 UNCONSTRAINED OPTIMIZATION; 2.3 CONSTRAINED OPTIMIZATION; 2.4 SUMMARY; BIBLIOGRAPHY; Chapter 3 Probability Metrics; 3.1 INTRODUCTION 3.2 MEASURING DISTANCES: THE DISCRETE CASE3.3 PRIMARY, SIMPLE, AND COMPOUND METRICS; 3.4 SUMMARY; 3.5 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 4 Ideal Probability Metrics; 4.1 INTRODUCTION; 4.2 THE CLASSICAL CENTRAL LIMIT THEOREM; 4.3 THE GENERALIZED CENTRAL LIMIT THEOREM; 4.4 CONSTRUCTION OF IDEAL PROBABILITY METRICS; 4.5 SUMMARY; 4.6 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 5 Choice under Uncertainty; 5.1 INTRODUCTION; 5.2 EXPECTED UTILITY THEORY; 5.3 STOCHASTIC DOMINANCE; 5.4 PROBABILITY METRICS AND STOCHASTIC DOMINANCE; 5.5 SUMMARY; 5.6 TECHNICAL APPENDIX; BIBLIOGRAPHY Chapter 6 Risk and Uncertainty6.1 INTRODUCTION; 6.2 MEASURES OF DISPERSION; 6.3 PROBABILITY METRICS AND DISPERSION MEASURES; 6.4 MEASURES OF RISK; 6.5 RISK MEASURES AND DISPERSION MEASURES; 6.6 RISK MEASURES AND STOCHASTIC ORDERS; 6.7 SUMMARY; 6.8 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 7 Average Value-at-Risk; 7.1 INTRODUCTION; 7.2 AVERAGE VALUE-AT-RISK; 7.3 AVaR ESTIMATION FROM A SAMPLE; 7.4 COMPUTING PORTFOLIO AVaR IN PRACTICE; 7.5 BACKTESTING OF AVaR; 7.6 SPECTRAL RISK MEASURES; 7.7 RISK MEASURES AND PROBABILITY METRICS; 7.8 SUMMARY; 7.9 TECHNICAL APPENDIX; BIBLIOGRAPHY Chapter 8 Optimal Portfolios8.1 INTRODUCTION; 8.2 MEAN-VARIANCE ANALYSIS; 8.3 MEAN-RISK ANALYSIS; 8.4 SUMMARY; 8.5 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 9 Benchmark Tracking Problems; 9.1 INTRODUCTION; 9.2 THE TRACKING ERROR PROBLEM; 9.3 RELATION TO PROBABILITY METRICS; 9.4 EXAMPLES OF r.d. METRICS; 9.5 NUMERICAL EXAMPLE; 9.6 SUMMARY; 9.7 TECHNICAL APPENDIX; BIBLIOGRAPHY; Chapter 10 Performance Measures; 10.1 INTRODUCTION; 10.2 REWARD-TO-RISK RATIOS; 10.3 REWARD-TO-VARIABILITY RATIOS; 10.4 SUMMARY; 10.5 TECHNICAL APPENDIX; BIBLIOGRAPHY; Index
Record Nr.	UNINA-9910461561503321

Edizione	[1st edition]
Pubbl/distr/stampa	Amsterdam ; ; Oxford, : Butterworth-Heinemann, 2003
Descrizione fisica	1 online resource (384 p.)
Disciplina	332.6
Altri autori (Persone)	SatchellS (Stephen) ScowcroftAlan
Collana	Butterworth-Heinemann finance
Soggetto topico	Portfolio management Portfolio management - Mathematical models Investments
Soggetto genere / forma	Electronic books.
ISBN	1-280-96633-5 9786610966332 1-4175-0763-2 0-08-047184-6
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	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 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 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? 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 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 7.12 Appendix 3: The Effects of Simple Holding Constraints on Expected Distribution of Asset Holding Weights
Record Nr.	UNINA-9910456029303321

Autore	Michaud Richard O. <1941->
Edizione	[2nd ed.]
Pubbl/distr/stampa	New York, : Oxford University Press, 2008
Descrizione fisica	1 online resource (145 p.)
Disciplina	332.6
Altri autori (Persone)	MichaudRobert O
Collana	Financial management association survey and synthesis series
Soggetto topico	Investment analysis - Mathematical models Portfolio management - Mathematical models
Soggetto genere / forma	Electronic books.
ISBN	0-19-988719-5 1-281-16231-0 9786611162313 0-19-971579-3 1-4356-3890-5
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Contents; 1 Introduction; Markowitz Efficiency; An Asset Management Tool; Traditional Objections; The Most Important Limitations; Resolving the Limitations of Mean-Variance Optimization; Illustrating the Techniques; 2 Classic Mean-Variance Optimization; Portfolio Risk and Return; Defining Markowitz Efficiency; Optimization Constraints; The Residual Risk-Return Efficient Frontier; Computer Algorithms; Asset Allocation Versus Equity Portfolio Optimization; A Global Asset Allocation Example; Reference Portfolios and Portfolio Analysis; Return Premium Efficient Frontiers Appendix: Mathematical Formulation of MV Efficiency3 Traditional Criticisms and Alternatives; Alternative Measures of Risk; Utility Function Optimization; Multiperiod Investment Horizons; Asset-Liability Financial Planning Studies; Linear Programming Optimization; 4 Unbounded MV Portfolio Efficiency; Unbounded MV Optimization; The Fundamental Limitations of Unbounded MV Efficiency; Repeating Jobson and Korkie; Implications of Jobson and Korkie Analysis; Statistical MV Efficiency and Implications; 5 Linear Constrained MV Efficiency; Linear Constraints; Efficient Frontier Variance Rank-Associated Efficient PortfoliosHow Practical an Investment Tool?; 6 The Resampled Efficient FrontierTM; Efficient Frontier Statistical Analysis; Properties of Resampled Efficient Frontier Portfolios; True and Estimated Optimization Inputs; Simulation Proofs of Resampled Efficiency Optimization; Why Does It Work; Certainty Level and RE Optimality; FC Level Applications; The REF Maximum Return Point (MRP); Implications for Asset Management; Conclusion; Appendix A: Rank- Versus λ-Associated RE Portfolios; Appendix B: Robert's Hedgehog; 7 Portfolio Rebalancing, Analysis, and Monitoring Resampled Efficiency and Distance FunctionsPortfolio Need-to-Trade Probability; Meta-Resampling Portfolio Rebalancing; Portfolio Monitoring and Analysis; Conclusion; Appendix: Confidence Region for the Sample Mean Vector; 8 Input Estimation and Stein Estimators; Admissible Estimators; Bayesian Procedures and Priors; Four Stein Estimators; James-Stein Estimator; James-Stein MV Efficiency; Out-of-Sample James-Stein Estimation; Frost-Savarino Estimator; Covariance Estimation; Stein Covariance Estimation; Utility Functions and Input Estimation; Ad Hoc Estimators; Stein Estimation Caveats ConclusionsAppendix: Ledoit Covariance Estimation; 9 Benchmark Mean-Variance Optimization; Benchmark-Relative Optimization Characteristics; Tracking Error Optimization and Constraints; Constraint Alternatives; Roll's Analysis; Index Efficiency; A Simple Benchmark-Relative Framework; Long-Short Investing; Conclusion; 10 Investment Policy and Economic Liabilities; Misusing Optimization; Economic Liability Models; Endowment Fund Investment Policy; Pension Liabilities and Benchmark Optimization; Limitations of Actuarial Liability Estimation; Current Pension Liabilities Total and Variable Pension Liabilities
Record Nr.	UNINA-9910451508403321