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Stochastic programming [[electronic resource] ] : applications in finance, energy, planning and logistics / / [edited by] Horand Gassmann, William Ziemba
| Stochastic programming [[electronic resource] ] : applications in finance, energy, planning and logistics / / [edited by] Horand Gassmann, William Ziemba |
| Pubbl/distr/stampa | Singapore ; ; Hackensack, NJ, : World Scientific, c2013 |
| Descrizione fisica | 1 online resource (549 p.) |
| Disciplina | 519.7 |
| Altri autori (Persone) |
GassmannHorand
ZiembaW. T |
| Collana | World Scientific series in finance |
| Soggetto topico |
Mathematical optimization
Mathematical optimization - Industrial applications Stochastic processes - Econometric models Stochastic programming Decision making Uncertainty |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-90005-X
981-4407-51-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Acknowledgements; List of Contributors; Preface; Books and Collections of Papers on Stochastic Programming; Contents; 1. Introduction and Summary; Part I. Papers in Finance; 2. Longevity Risk Management for Individual Investors Woo Chang Kim, John M. Mulvey, Koray D. Simsek and Min Jeong Kim; 1 Introduction; 2 Model; 3 Numerical results; 3.1 First example: Retirement planning without longevity risk consideration; 3.2 Second example: Impact of longevity risk to retirement planning; 3.3 Third example: Longevity risks in pension benefits; 4 Conclusions; References
3. Optimal Stochastic Programming-Based Personal Financial Planning with Intermediate and Long-Term Goals Vittorio Moriggia, Giorgio Consigli and Gaetano Iaquinta1 Introduction; 2 The asset-liability management model; 2.1 Individual wealth, consumption and investment targets; 2.2 Random coefficients and scenarios; 2.3 The optimization problem; 3 Numerical implementation and case study; 3.1 Decision tool modular structure; 3.1.1 Individual policy statement; 3.1.2 Scenario manager; 3.1.3 Output; 3.2 Case study; 3.2.1 Optimal solutions; 4 Conclusion; References 4. Intertemporal Surplus Management with Jump Risks Mareen Benk1 Introduction; 2 An intertemporal surplus management model with jump risks - a three-fund theorem; 3 Risk preference, and funding ratio; 4 Conclusions; Appendix I: Derivation of the asset specific risk factor of the first jump component; Appendix II: Derivation of equation (16); Appendix III: Derivation of equation (17); References; 5. Jump-Diffusion Risk-Sensitive Benchmarked Asset Management Mark Davis and Sebastien Lleo; 1 Introduction; 2 Analytical setting; 2.1 Factor dynamics; 2.2 Asset market dynamics 2.3 Benchmark modelling2.4 Portfolio dynamics; 2.5 Investment constraints; 2.6 Problem formulation; 3 Dynamic programming and the value function; 3.1 The risk-sensitive control problems under Ph; 3.2 Properties of the value function; 3.3 Main result; 4 Existence of a classical (C1,2) solution under affine drift assumptions; 5 Existence of a classical (C1,2) solution under standard control assumptions; 6 Verification; 6.1 The unique maximizer of the supremum (60) is the optimal control, i.e. h*(t,Xt) = h (t,Xt,D (t,Xt)); 6.2 Verification; 7 Conclusion; References 6. Dynamic Portfolio Optimization under Regime-Based Firm Strength Chanaka Edirisinghe and Xin Zhang1 Introduction; 2 DEA-based relative firm strength; 2.1 Financial DEA model; 2.2 Parameters of RFS; 2.3 Correlation analysis; 3 Modeling market regimes; 3.1 Regime analysis (1971-2010); 3.2 Regime-based firm-RFS; 4 Portfolio optimization under regime-based RFS; 4.1 RFS-based stock selections; 4.2 Decisions under regime-scenarios; 4.3 Transactions cost model; 4.4 Budget constraints; 4.5 Risk-return framework; 4.6 Two-period optimization model; 5 Model application 5.1 RFS estimation and firm selections |
| Record Nr. | UNINA-9910463664903321 |
| Singapore ; ; Hackensack, NJ, : World Scientific, c2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Stochastic programming [[electronic resource] ] : applications in finance, energy, planning and logistics / / [edited by] Horand Gassmann, William Ziemba
| Stochastic programming [[electronic resource] ] : applications in finance, energy, planning and logistics / / [edited by] Horand Gassmann, William Ziemba |
| Pubbl/distr/stampa | Singapore ; ; Hackensack, NJ, : World Scientific, c2013 |
| Descrizione fisica | 1 online resource (549 p.) |
| Disciplina | 519.7 |
| Altri autori (Persone) |
GassmannHorand
ZiembaW. T |
| Collana | World Scientific series in finance |
| Soggetto topico |
Mathematical optimization
Mathematical optimization - Industrial applications Stochastic processes - Econometric models Stochastic programming Decision making Uncertainty |
| ISBN |
1-283-90005-X
981-4407-51-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Acknowledgements; List of Contributors; Preface; Books and Collections of Papers on Stochastic Programming; Contents; 1. Introduction and Summary; Part I. Papers in Finance; 2. Longevity Risk Management for Individual Investors Woo Chang Kim, John M. Mulvey, Koray D. Simsek and Min Jeong Kim; 1 Introduction; 2 Model; 3 Numerical results; 3.1 First example: Retirement planning without longevity risk consideration; 3.2 Second example: Impact of longevity risk to retirement planning; 3.3 Third example: Longevity risks in pension benefits; 4 Conclusions; References
3. Optimal Stochastic Programming-Based Personal Financial Planning with Intermediate and Long-Term Goals Vittorio Moriggia, Giorgio Consigli and Gaetano Iaquinta1 Introduction; 2 The asset-liability management model; 2.1 Individual wealth, consumption and investment targets; 2.2 Random coefficients and scenarios; 2.3 The optimization problem; 3 Numerical implementation and case study; 3.1 Decision tool modular structure; 3.1.1 Individual policy statement; 3.1.2 Scenario manager; 3.1.3 Output; 3.2 Case study; 3.2.1 Optimal solutions; 4 Conclusion; References 4. Intertemporal Surplus Management with Jump Risks Mareen Benk1 Introduction; 2 An intertemporal surplus management model with jump risks - a three-fund theorem; 3 Risk preference, and funding ratio; 4 Conclusions; Appendix I: Derivation of the asset specific risk factor of the first jump component; Appendix II: Derivation of equation (16); Appendix III: Derivation of equation (17); References; 5. Jump-Diffusion Risk-Sensitive Benchmarked Asset Management Mark Davis and Sebastien Lleo; 1 Introduction; 2 Analytical setting; 2.1 Factor dynamics; 2.2 Asset market dynamics 2.3 Benchmark modelling2.4 Portfolio dynamics; 2.5 Investment constraints; 2.6 Problem formulation; 3 Dynamic programming and the value function; 3.1 The risk-sensitive control problems under Ph; 3.2 Properties of the value function; 3.3 Main result; 4 Existence of a classical (C1,2) solution under affine drift assumptions; 5 Existence of a classical (C1,2) solution under standard control assumptions; 6 Verification; 6.1 The unique maximizer of the supremum (60) is the optimal control, i.e. h*(t,Xt) = h (t,Xt,D (t,Xt)); 6.2 Verification; 7 Conclusion; References 6. Dynamic Portfolio Optimization under Regime-Based Firm Strength Chanaka Edirisinghe and Xin Zhang1 Introduction; 2 DEA-based relative firm strength; 2.1 Financial DEA model; 2.2 Parameters of RFS; 2.3 Correlation analysis; 3 Modeling market regimes; 3.1 Regime analysis (1971-2010); 3.2 Regime-based firm-RFS; 4 Portfolio optimization under regime-based RFS; 4.1 RFS-based stock selections; 4.2 Decisions under regime-scenarios; 4.3 Transactions cost model; 4.4 Budget constraints; 4.5 Risk-return framework; 4.6 Two-period optimization model; 5 Model application 5.1 RFS estimation and firm selections |
| Record Nr. | UNINA-9910788622703321 |
| Singapore ; ; Hackensack, NJ, : World Scientific, c2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Stochastic programming : applications in finance, energy, planning and logistics / / [edited by] Horand Gassmann, William Ziemba
| Stochastic programming : applications in finance, energy, planning and logistics / / [edited by] Horand Gassmann, William Ziemba |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore ; ; Hackensack, NJ, : World Scientific, c2013 |
| Descrizione fisica | 1 online resource (549 p.) |
| Disciplina | 519.7 |
| Altri autori (Persone) |
GassmannHorand
ZiembaW. T |
| Collana | World Scientific series in finance |
| Soggetto topico |
Mathematical optimization
Mathematical optimization - Industrial applications Stochastic processes - Econometric models Stochastic programming Decision making Uncertainty |
| ISBN |
1-283-90005-X
981-4407-51-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Acknowledgements; List of Contributors; Preface; Books and Collections of Papers on Stochastic Programming; Contents; 1. Introduction and Summary; Part I. Papers in Finance; 2. Longevity Risk Management for Individual Investors Woo Chang Kim, John M. Mulvey, Koray D. Simsek and Min Jeong Kim; 1 Introduction; 2 Model; 3 Numerical results; 3.1 First example: Retirement planning without longevity risk consideration; 3.2 Second example: Impact of longevity risk to retirement planning; 3.3 Third example: Longevity risks in pension benefits; 4 Conclusions; References
3. Optimal Stochastic Programming-Based Personal Financial Planning with Intermediate and Long-Term Goals Vittorio Moriggia, Giorgio Consigli and Gaetano Iaquinta1 Introduction; 2 The asset-liability management model; 2.1 Individual wealth, consumption and investment targets; 2.2 Random coefficients and scenarios; 2.3 The optimization problem; 3 Numerical implementation and case study; 3.1 Decision tool modular structure; 3.1.1 Individual policy statement; 3.1.2 Scenario manager; 3.1.3 Output; 3.2 Case study; 3.2.1 Optimal solutions; 4 Conclusion; References 4. Intertemporal Surplus Management with Jump Risks Mareen Benk1 Introduction; 2 An intertemporal surplus management model with jump risks - a three-fund theorem; 3 Risk preference, and funding ratio; 4 Conclusions; Appendix I: Derivation of the asset specific risk factor of the first jump component; Appendix II: Derivation of equation (16); Appendix III: Derivation of equation (17); References; 5. Jump-Diffusion Risk-Sensitive Benchmarked Asset Management Mark Davis and Sebastien Lleo; 1 Introduction; 2 Analytical setting; 2.1 Factor dynamics; 2.2 Asset market dynamics 2.3 Benchmark modelling2.4 Portfolio dynamics; 2.5 Investment constraints; 2.6 Problem formulation; 3 Dynamic programming and the value function; 3.1 The risk-sensitive control problems under Ph; 3.2 Properties of the value function; 3.3 Main result; 4 Existence of a classical (C1,2) solution under affine drift assumptions; 5 Existence of a classical (C1,2) solution under standard control assumptions; 6 Verification; 6.1 The unique maximizer of the supremum (60) is the optimal control, i.e. h*(t,Xt) = h (t,Xt,D (t,Xt)); 6.2 Verification; 7 Conclusion; References 6. Dynamic Portfolio Optimization under Regime-Based Firm Strength Chanaka Edirisinghe and Xin Zhang1 Introduction; 2 DEA-based relative firm strength; 2.1 Financial DEA model; 2.2 Parameters of RFS; 2.3 Correlation analysis; 3 Modeling market regimes; 3.1 Regime analysis (1971-2010); 3.2 Regime-based firm-RFS; 4 Portfolio optimization under regime-based RFS; 4.1 RFS-based stock selections; 4.2 Decisions under regime-scenarios; 4.3 Transactions cost model; 4.4 Budget constraints; 4.5 Risk-return framework; 4.6 Two-period optimization model; 5 Model application 5.1 RFS estimation and firm selections |
| Record Nr. | UNINA-9910826068703321 |
| Singapore ; ; Hackensack, NJ, : World Scientific, c2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
