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Autonomous road vehicle path planning and tracking control / / Levent Guvenc [and three others]
| Autonomous road vehicle path planning and tracking control / / Levent Guvenc [and three others] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] |
| Descrizione fisica | 1 online resource (259 pages) |
| Disciplina | 629.04/6 |
| Collana | IEEE Press Series on Control Systems Theory and Applications Ser. |
| Soggetto topico |
Automated vehicles - Design and construction
Automated vehicles - Collision avoidance systems Mathematical optimization - Industrial applications |
| ISBN |
1-119-74796-1
1-119-74797-X 1-119-74795-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Contents -- About the Authors -- Preface -- List of Abbreviations -- Chapter 1 Introduction -- 1.1 Motivation and Introduction -- 1.2 History of Automated Driving -- 1.3 ADAS to Autonomous Driving -- 1.4 Autonomous Driving Architectures -- 1.5 Cybersecurity Considerations -- 1.6 Organization and Scope of the Book -- 1.7 Chapter Summary and Concluding Remarks -- References -- Chapter 2 Vehicle, Path, and Path Tracking Models -- 2.1 Tire Force Model -- 2.1.1 Introduction -- 2.1.2 Tire Forces/Moments and Slip -- 2.1.3 Longitudinal Tire Force Modeling -- 2.1.4 Lateral Tire Force Modeling -- 2.1.5 Self‐aligning Moment Model -- 2.1.6 Coupling of Tire Forces -- 2.2 Vehicle Longitudinal Dynamics Model -- 2.3 Vehicle Lateral Dynamics Model -- 2.3.1 Geometry of Cornering -- 2.3.2 Single‐Track Lateral Vehicle Model -- 2.3.3 Augmented Single‐Track Lateral Vehicle Model -- 2.3.4 Linearized Single Track Lateral Vehicle Model -- 2.4 Path Model -- 2.5 Pure Pursuit: Geometry‐Based Low‐Speed Path Tracking -- 2.6 Stanley Method for Path Tracking -- 2.7 Path Tracking in Reverse Driving and Parking -- 2.8 Chapter Summary and Concluding Remarks -- References -- Chapter 3 Simulation, Experimentation, and Estimation Overview -- 3.1 Introduction to the Simulation‐Based Development and Evaluation Process -- 3.2 Model‐in‐the‐Loop Simulation -- 3.2.1 Linear and Nonlinear Vehicle Simulation Models -- 3.2.2 Higher Fidelity Vehicle Simulation Models -- 3.3 Virtual Environments Used in Simulation -- 3.3.1 Road Network Creation -- 3.3.2 Driving Environment Construction -- 3.3.3 Capabilities -- 3.4 Hardware‐in‐the‐Loop Simulation -- 3.5 Experimental Vehicle Testbeds -- 3.5.1 Unified Approach -- 3.5.2 Unified AV Functions and Sensors Library -- 3.6 Estimation -- 3.6.1 Estimation of the Effective Tire Radius.
3.6.2 Slip Slope Method for Road Friction Coefficient Estimation -- 3.6.3 Results and Discussion -- 3.7 Chapter Summary and Concluding Remarks -- References -- Chapter 4 Path Description and Generation -- 4.1 Introduction -- 4.2 Discrete Waypoint Representation -- 4.3 Parametric Path Description -- 4.3.1 Clothoids -- 4.3.2 Bezier Curves -- 4.3.3 Polynomial Spline Description -- 4.4 Tracking Error Calculation -- 4.4.1 Tracking Error Computation for a Discrete Waypoint Path Representation -- 4.4.2 Tracking Error Computation for a Spline Path Representation -- 4.5 Chapter Summary and Concluding Remarks -- References -- Chapter 5 Collision Free Path Planning -- 5.1 Introduction -- 5.2 Elastic Band Method -- 5.2.1 Path Structure -- 5.2.2 Calculation of Forces -- 5.2.3 Reaching Equilibrium Point -- 5.2.4 Selected Scenarios -- 5.2.5 Results -- 5.3 Path Planning with Minimum Curvature Variation -- 5.3.1 Optimization Based on G2‐Quintic Splines Path Description -- 5.3.2 Reduction of Computation Cost Using Lookup Tables -- 5.3.3 Geometry‐Based Collision‐Free Target Points Generation -- 5.3.4 Simulation Results -- 5.4 Model‐Based Trajectory Planning -- 5.4.1 Problem Formulation -- 5.4.2 Parameterized Vehicle Control -- 5.4.3 Constrained Optimization on Curvature Control -- 5.4.4 Sampling of the Longitudinal Movements -- 5.4.5 Trajectory Evaluation and Selection -- 5.4.6 Integration of Road Friction Coefficient Estimation for Safety Enhancement -- 5.4.7 Simulation Results in Complex Scenarios -- 5.5 Chapter Summary and Concluding Remarks -- References -- Chapter 6 Path‐Tracking Model Regulation -- 6.1 Introduction -- 6.2 DOB Design and Frequency Response Analysis -- 6.2.1 DOB Derivation and Loop Structure -- 6.2.2 Application Examples -- 6.2.3 Disturbance Rejection Comparison -- 6.3 Q Filter Design -- 6.4 Time Delay Performance. 6.5 Chapter Summary and Concluding Remarks -- References -- Chapter 7 Robust Path Tracking Control -- 7.1 Introduction -- 7.2 Model Predictive Control for Path Following -- 7.2.1 Formulation of Linear Adaptive MPC Problem -- 7.2.2 Estimation of Lateral Velocity -- 7.2.3 Experimental Results -- 7.3 Design Methodology for Robust Gain‐Scheduling Law -- 7.3.1 Problem Formulation -- 7.3.2 Design via Optimization in Linear Matrix Inequalities Form -- 7.3.3 Parameter‐Space Gain‐Scheduling Methodology -- 7.4 Robust Gain‐Scheduling Application to Path‐Tracking Control -- 7.4.1 Car Steering Model and Parameter Uncertainty -- 7.4.2 Controller Structure and Design Parameters -- 7.4.3 Application of Parameter‐Space Gain‐Scheduling -- 7.4.4 Comparative Study of LMI Design -- 7.4.5 Experimental Results and Discussions -- 7.5 Add‐on Vehicle Stability Control for Autonomous Driving -- 7.5.1 Direct Yaw Moment Control Strategies -- 7.5.2 Direct Yaw Moment Distribution via Differential Braking -- 7.5.3 Simulation Results and Discussion -- 7.6 Chapter Summary and Concluding Remarks -- References -- Chapter 8 Summary and Conclusions -- 8.1 Summary -- 8.2 Conclusions -- Index -- Books in the IEEE Press Series on Control Systems Theoryand Applications -- EULA. |
| Record Nr. | UNINA-9910555143603321 |
| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Autonomous road vehicle path planning and tracking control / / Levent Guvenc [and three others]
| Autonomous road vehicle path planning and tracking control / / Levent Guvenc [and three others] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] |
| Descrizione fisica | 1 online resource (259 pages) |
| Disciplina | 629.04/6 |
| Collana | IEEE Press Series on Control Systems Theory and Applications |
| Soggetto topico |
Automated vehicles - Design and construction
Automated vehicles - Collision avoidance systems Mathematical optimization - Industrial applications |
| ISBN |
1-119-74796-1
1-119-74797-X 1-119-74795-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright -- Contents -- About the Authors -- Preface -- List of Abbreviations -- Chapter 1 Introduction -- 1.1 Motivation and Introduction -- 1.2 History of Automated Driving -- 1.3 ADAS to Autonomous Driving -- 1.4 Autonomous Driving Architectures -- 1.5 Cybersecurity Considerations -- 1.6 Organization and Scope of the Book -- 1.7 Chapter Summary and Concluding Remarks -- References -- Chapter 2 Vehicle, Path, and Path Tracking Models -- 2.1 Tire Force Model -- 2.1.1 Introduction -- 2.1.2 Tire Forces/Moments and Slip -- 2.1.3 Longitudinal Tire Force Modeling -- 2.1.4 Lateral Tire Force Modeling -- 2.1.5 Self‐aligning Moment Model -- 2.1.6 Coupling of Tire Forces -- 2.2 Vehicle Longitudinal Dynamics Model -- 2.3 Vehicle Lateral Dynamics Model -- 2.3.1 Geometry of Cornering -- 2.3.2 Single‐Track Lateral Vehicle Model -- 2.3.3 Augmented Single‐Track Lateral Vehicle Model -- 2.3.4 Linearized Single Track Lateral Vehicle Model -- 2.4 Path Model -- 2.5 Pure Pursuit: Geometry‐Based Low‐Speed Path Tracking -- 2.6 Stanley Method for Path Tracking -- 2.7 Path Tracking in Reverse Driving and Parking -- 2.8 Chapter Summary and Concluding Remarks -- References -- Chapter 3 Simulation, Experimentation, and Estimation Overview -- 3.1 Introduction to the Simulation‐Based Development and Evaluation Process -- 3.2 Model‐in‐the‐Loop Simulation -- 3.2.1 Linear and Nonlinear Vehicle Simulation Models -- 3.2.2 Higher Fidelity Vehicle Simulation Models -- 3.3 Virtual Environments Used in Simulation -- 3.3.1 Road Network Creation -- 3.3.2 Driving Environment Construction -- 3.3.3 Capabilities -- 3.4 Hardware‐in‐the‐Loop Simulation -- 3.5 Experimental Vehicle Testbeds -- 3.5.1 Unified Approach -- 3.5.2 Unified AV Functions and Sensors Library -- 3.6 Estimation -- 3.6.1 Estimation of the Effective Tire Radius.
3.6.2 Slip Slope Method for Road Friction Coefficient Estimation -- 3.6.3 Results and Discussion -- 3.7 Chapter Summary and Concluding Remarks -- References -- Chapter 4 Path Description and Generation -- 4.1 Introduction -- 4.2 Discrete Waypoint Representation -- 4.3 Parametric Path Description -- 4.3.1 Clothoids -- 4.3.2 Bezier Curves -- 4.3.3 Polynomial Spline Description -- 4.4 Tracking Error Calculation -- 4.4.1 Tracking Error Computation for a Discrete Waypoint Path Representation -- 4.4.2 Tracking Error Computation for a Spline Path Representation -- 4.5 Chapter Summary and Concluding Remarks -- References -- Chapter 5 Collision Free Path Planning -- 5.1 Introduction -- 5.2 Elastic Band Method -- 5.2.1 Path Structure -- 5.2.2 Calculation of Forces -- 5.2.3 Reaching Equilibrium Point -- 5.2.4 Selected Scenarios -- 5.2.5 Results -- 5.3 Path Planning with Minimum Curvature Variation -- 5.3.1 Optimization Based on G2‐Quintic Splines Path Description -- 5.3.2 Reduction of Computation Cost Using Lookup Tables -- 5.3.3 Geometry‐Based Collision‐Free Target Points Generation -- 5.3.4 Simulation Results -- 5.4 Model‐Based Trajectory Planning -- 5.4.1 Problem Formulation -- 5.4.2 Parameterized Vehicle Control -- 5.4.3 Constrained Optimization on Curvature Control -- 5.4.4 Sampling of the Longitudinal Movements -- 5.4.5 Trajectory Evaluation and Selection -- 5.4.6 Integration of Road Friction Coefficient Estimation for Safety Enhancement -- 5.4.7 Simulation Results in Complex Scenarios -- 5.5 Chapter Summary and Concluding Remarks -- References -- Chapter 6 Path‐Tracking Model Regulation -- 6.1 Introduction -- 6.2 DOB Design and Frequency Response Analysis -- 6.2.1 DOB Derivation and Loop Structure -- 6.2.2 Application Examples -- 6.2.3 Disturbance Rejection Comparison -- 6.3 Q Filter Design -- 6.4 Time Delay Performance. 6.5 Chapter Summary and Concluding Remarks -- References -- Chapter 7 Robust Path Tracking Control -- 7.1 Introduction -- 7.2 Model Predictive Control for Path Following -- 7.2.1 Formulation of Linear Adaptive MPC Problem -- 7.2.2 Estimation of Lateral Velocity -- 7.2.3 Experimental Results -- 7.3 Design Methodology for Robust Gain‐Scheduling Law -- 7.3.1 Problem Formulation -- 7.3.2 Design via Optimization in Linear Matrix Inequalities Form -- 7.3.3 Parameter‐Space Gain‐Scheduling Methodology -- 7.4 Robust Gain‐Scheduling Application to Path‐Tracking Control -- 7.4.1 Car Steering Model and Parameter Uncertainty -- 7.4.2 Controller Structure and Design Parameters -- 7.4.3 Application of Parameter‐Space Gain‐Scheduling -- 7.4.4 Comparative Study of LMI Design -- 7.4.5 Experimental Results and Discussions -- 7.5 Add‐on Vehicle Stability Control for Autonomous Driving -- 7.5.1 Direct Yaw Moment Control Strategies -- 7.5.2 Direct Yaw Moment Distribution via Differential Braking -- 7.5.3 Simulation Results and Discussion -- 7.6 Chapter Summary and Concluding Remarks -- References -- Chapter 8 Summary and Conclusions -- 8.1 Summary -- 8.2 Conclusions -- Index -- Books in the IEEE Press Series on Control Systems Theoryand Applications -- EULA. |
| Record Nr. | UNINA-9910829996303321 |
| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2022] | ||
| 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 |
| 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 | ||
| ||
