Stochastic optimization models in finance /

Mostrar otras versiones (3)

Stochastic Optimization Models in Finance.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Ziemba, W. T. (Compilador), Vickson, R. G. (Compilador)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York : Academic Press, [1975]
Colección:Economic theory and mathematical economics.
Temas:
Finance.
Mathematical optimization.
Stochastic processes.
Finance > Mathematical models.
Stochastic Processes
Finances > Mod�eles math�ematiques.
Optimisation math�ematique.
Processus stochastiques.
Finances.
finance.
BUSINESS & ECONOMICS > Finance.
Finance > Mathematical models
Finance
Mathematical optimization
Stochastic processes
Entscheidungstheorie
Investitionsentscheidung
Portfolio Selection
Stochastische Optimierung
Unsicherheit
Finanzierung
Finanzmathematik
banken
banks
valuta
currencies
finance
public finance
stochastische processen
stochastic processes
Financial Economics
Aufsatzsammlung.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover; Stochastic Optimization Models in Finance; Copyright Page; Dedication; Table of Contents; PREFACE; ACKNOWLEDGMENTS; Part I: Mathematical Tools; INTRODUCTION; I. Expected Utility Theory; II. Convexity and the Kuhn-Tucker Conditions; III. Dynamic Programming; SECTION1: EXPECTED UTILITY THEORY; CHAPTER 1. A GENERAL THEORY OF SUBJECTIVE PROBABILITIESAND EXPECTED UTILITIES; 1. Introduction; 2. Definitions andnotation; 3. Axioms and summarytheorem; 4. Theorems; 5. Proof of Theorem3; 6. Proof of Theorem4; SECTION2: CONVEXITY AND THE KUHN-TUCKERCONDITIONS; CHAPTER2. PSEUDO-CONVEX FUNCTIONS
  • Abstract1. Introduction; 2. Properties of pseudo-convex functions andapplications; 3. Remarks on pseudo-convexfunctions; 4. Acknowledgement; CHAPTER3. CONVEXITY, PSEUDO-CONVEXITY AND QUASI-CONVEXITY OF COMPOSITE FUNCTIONS; ABSTRACT; Preliminaries; Principal result; Applications; SECTION3: DYNAMIC PROGRAMMING; Chapter4. Introduction to Dynamic Programming; I. Introduction; II. Sequential Decision Processes; III. Terminating Process; IV. The Main Theorem and an Algorithm; V. Nonterminating Processes; ACKNOWLEDGMENT; REFERENCES; CHAPTER5. COMPUTATIONAL AND REVIEW EXERCISES; Exercise Source Notes
  • CHAPTER6. MIND-EXPANDING EXERCISESExercise Source Notes; Part II: Qualitative Economic Results; INTRODUCTION; I. Stochastic Dominance; II. Measures of Risk Aversion; III. Separation Theorems; IV. Additional Reading Material; SECTION1: STOCHASTIC DOMINANCE; Chapter 1. The Efficiency Analysis of ChoicesInvolvingRisk; I. INTRODUCTION; II. UNRESTRICTED UTILITY-THE GENERALEFFICIENCY CRITERION; III. EFFICIENCY IN THE FACE OF RISK AVERSION; IV. THE LIMITATIONS OF THE MEAN-VARIANCEEFFICIENCY CRITERION; V. CONCLUSION; REFERENCES; Chapter 2. A Unified Approach to Stochastic Dominance
  • I. Introduction to Stochastic DominanceII. Examples of Stochastic Dominance Relations; III. Probabilistic Content of Stochastic Dominance; REFERENCES; SECTION2: MEASURES OF RISK AVERSION; CHAPTER3. RISK AVERSION IN THE SMALL AND IN THE LARGE; 1. SUMMARY AND INTRODUCTION; 2. THE RISK PREMIUM; 3. LOCAL RISK AVERSION; 4. CONCAVITY; 5. COMPARATIVE RISK AVERSION; 6. CONSTANT RISK AVERSION; 7. INCREASING AND DECREASING RISK AVERSION; 8. OPERATIONS WHICH PRESERVE DECREASING RISK AVERSION; 9. EXAMPLES; 10. PROPORTIONAL RISK AVERSION; 11. CONSTANT PROPORTIONAL RISK AVERSION
  • 12. INCREASING AND DECREASING PROPORTIONAL RISK AVERSION13. RELATED WORK OF ARROW; ADDENDUM; SECTION3: SEPARATION THEOREMS; CHAPTER 4. THE VALUATION OF RISK ASSETS AND THE SELECTION OF RISKY INVESTMENTS IN STOCKPORTFOLIOS AND CAPITAL BUDGETS; Introduction and Preview of Some Conclusions; I
  • Portfolio Selection for an Individual Investor:The Separation Theorem; II -Portfolio Selection: TheOptimal Stock Mix; Ill Risk Premiums and Other Properties of Stocks Held Long or Shortin Optimal Portfolios
  • IV
  • Market Prices of Shares Implied by Shareholder Optimization in Purely Competitive MarketsUnder Idealized Uncertainty

Ejemplares similares