Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach

Wiley - 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, probability theory, stochastic processes, Measure, and Mathematical Finance: A Problem-Oriented Approach presents important concepts and results in measure theory, Probability, and stochastic calculus.

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 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.

Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach - 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, and mathematical finance: a problem-oriented approach is an ideal textbook for introductory quantitative courses in business, Probability, Probability, 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, Measure, stochastic processes, probability theory, economics, and Mathematical Finance features: A comprehensive list of concepts and theorems from measure theory, and mathematical finance at the upper-undergraduate and graduate levels.

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.


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