Applied Stochastic Models and Control for Finance and Insurance 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Applied Stochastic Models and Control for Finance and Insurance

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Charles S. Tapiero 作者
Springer
译者
1998-04-30 出版日期
354 页数
USD 229.00 价格
Hardcover
丛书系列
9780792381488 图书编码

Applied Stochastic Models and Control for Finance and Insurance 在线电子书 图书标签: STOCHASTIC  Finance  FINANCE   


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Applied Stochastic Models and Control for Finance and Insurance 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Applied Stochastic Models and Control for Finance and Insurance 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Applied Stochastic Models and Control for Finance and Insurance 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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Applied Stochastic Models and Control for Finance and Insurance 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Applied Stochastic Models and Control for Finance and Insurance 在线电子书 图书描述

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.

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