Applied Stochastic Models and Control for Finance and Insurance

  • Charles S. Tapiero

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Charles S. Tapiero
    Pages 1-40
  3. Charles S. Tapiero
    Pages 41-88
  4. Charles S. Tapiero
    Pages 89-146
  5. Charles S. Tapiero
    Pages 147-182
  6. Charles S. Tapiero
    Pages 183-235
  7. Charles S. Tapiero
    Pages 237-274
  8. Charles S. Tapiero
    Pages 275-306
  9. Back Matter
    Pages 307-341

About this book


Applied Stochastic Models and Control for Finance and Insurance presents at an introductory level some essential stochastic models applied in economics, finance and insurance. Markov chains, random walks, stochastic differential equations and other stochastic processes are used throughout the book and systematically applied to economic and financial applications. In addition, a dynamic programming framework is used to deal with some basic optimization problems.
The book begins by introducing problems of economics, finance and insurance which involve time, uncertainty and risk. A number of cases are treated in detail, spanning risk management, volatility, memory, the time structure of preferences, interest rates and yields, etc. The second and third chapters provide an introduction to stochastic models and their application. Stochastic differential equations and stochastic calculus are presented in an intuitive manner, and numerous applications and exercises are used to facilitate their understanding and their use in Chapter 3. A number of other processes which are increasingly used in finance and insurance are introduced in Chapter 4. In the fifth chapter, ARCH and GARCH models are presented and their application to modeling volatility is emphasized. An outline of decision-making procedures is presented in Chapter 6. Furthermore, we also introduce the essentials of stochastic dynamic programming and control, and provide first steps for the student who seeks to apply these techniques. Finally, in Chapter 7, numerical techniques and approximations to stochastic processes are examined.
This book can be used in business, economics, financial engineering and decision sciences schools for second year Master's students, as well as in a number of courses widely given in departments of statistics, systems and decision sciences.


Finance Markov Chains Markov chain Markov process Stochastic Differential Equations Stochastic Processes Stochastic calculus Stochastic model Stochastic models calculus modeling optimization random walk statistics stochastic process

Authors and affiliations

  • Charles S. Tapiero
    • 1
  1. 1.ESSECCergy PontoiseFrance

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