Measure, Probability, and Mathematical Finance

A Problem-Oriented Approach

Business & Finance, Economics, Statistics, Nonfiction, Science & Nature, Mathematics, Finance & Investing, Finance
Cover of the book Measure, Probability, and Mathematical Finance by Guojun Gan, Chaoqun Ma, Hong Xie, Wiley
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Author: Guojun Gan, Chaoqun Ma, Hong Xie ISBN: 9781118831984
Publisher: Wiley Publication: May 5, 2014
Imprint: Wiley Language: English
Author: Guojun Gan, Chaoqun Ma, Hong Xie
ISBN: 9781118831984
Publisher: Wiley
Publication: May 5, 2014
Imprint: Wiley
Language: English

An introduction to the mathematical theory and financial models developed and used on Wall Street

Providing both a theoretical and practical approach to the underlying mathematical theory behind financial models, Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach presents important concepts and results in measure theory, probability theory, stochastic processes, and stochastic calculus. Measure theory is indispensable to the rigorous development of probability theory and is also necessary to properly address martingale measures, the change of numeraire theory, and LIBOR market models. In addition, probability theory is presented to facilitate the development of stochastic processes, including martingales and Brownian motions, while stochastic processes and stochastic calculus are discussed to model asset prices and develop derivative pricing models.

The authors promote a problem-solving approach when applying mathematics in real-world situations, and readers are encouraged to address theorems and problems with mathematical rigor. In addition, Measure, Probability, and Mathematical Finance features:

  • A comprehensive list of concepts and theorems from measure theory, probability theory, stochastic processes, and stochastic calculus
  • Over 500 problems with hints and select solutions to reinforce basic concepts and important theorems
  • Classic derivative pricing models in mathematical finance that have been developed and published since the seminal work of Black and Scholes

Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach is an ideal textbook for introductory quantitative courses in business, economics, and mathematical finance at the upper-undergraduate and graduate levels. The book is also a useful reference for readers who need to build their mathematical skills in order to better understand the mathematical theory of derivative pricing models.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

An introduction to the mathematical theory and financial models developed and used on Wall Street

Providing both a theoretical and practical approach to the underlying mathematical theory behind financial models, Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach presents important concepts and results in measure theory, probability theory, stochastic processes, and stochastic calculus. Measure theory is indispensable to the rigorous development of probability theory and is also necessary to properly address martingale measures, the change of numeraire theory, and LIBOR market models. In addition, probability theory is presented to facilitate the development of stochastic processes, including martingales and Brownian motions, while stochastic processes and stochastic calculus are discussed to model asset prices and develop derivative pricing models.

The authors promote a problem-solving approach when applying mathematics in real-world situations, and readers are encouraged to address theorems and problems with mathematical rigor. In addition, Measure, Probability, and Mathematical Finance features:

Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach is an ideal textbook for introductory quantitative courses in business, economics, and mathematical finance at the upper-undergraduate and graduate levels. The book is also a useful reference for readers who need to build their mathematical skills in order to better understand the mathematical theory of derivative pricing models.

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