Stochastic Optimization Models in Finance
eBook - PDF

Stochastic Optimization Models in Finance

  1. 736 pages
  2. English
  3. PDF
  4. Only available on web
eBook - PDF

Stochastic Optimization Models in Finance

Book details
Table of contents
Citations

About This Book

Stochastic Optimization Models in Finance focuses on the applications of stochastic optimization models in finance, with emphasis on results and methods that can and have been utilized in the analysis of real financial problems. The discussions are organized around five themes: mathematical tools; qualitative economic results; static portfolio selection models; dynamic models that are reducible to static models; and dynamic models. This volume consists of five parts and begins with an overview of expected utility theory, followed by an analysis of convexity and the Kuhn-Tucker conditions. The reader is then introduced to dynamic programming; stochastic dominance; and measures of risk aversion. Subsequent chapters deal with separation theorems; existence and diversification of optimal portfolio policies; effects of taxes on risk taking; and two-period consumption models and portfolio revision. The book also describes models of optimal capital accumulation and portfolio selection. This monograph will be of value to mathematicians and economists as well as to those interested in economic theory and mathematical economics.

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Yes, you can access Stochastic Optimization Models in Finance by W. T. Ziemba,R. G. Vickson in PDF and/or ePUB format, as well as other popular books in Business & Finance. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2014
ISBN
9781483273990
Topic
Business
Subtopic
Finance
Index
Business

Table of contents

  1. Front Cover
  2. Stochastic Optimization Models in Finance
  3. Copyright Page
  4. Table of Contents
  5. Dedication
  6. PREFACE
  7. ACKNOWLEDGMENTS
  8. Part I: Mathematical Tools
  9. Part II: Qualitative Economic Results
  10. Part III: Static Portfolio Selection Models
  11. Part IV: Dynamic Models Reducible to Static Models
  12. Part V: Dynamic Models
  13. Bibliography
  14. INDEX