Stochastic Models of Financial Mathematics

Nonfiction, Science & Nature, Mathematics, Probability, Game Theory
Cover of the book Stochastic Models of Financial Mathematics by Vigirdas Mackevicius, Elsevier Science
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Author: Vigirdas Mackevicius ISBN: 9780081020869
Publisher: Elsevier Science Publication: November 8, 2016
Imprint: ISTE Press - Elsevier Language: English
Author: Vigirdas Mackevicius
ISBN: 9780081020869
Publisher: Elsevier Science
Publication: November 8, 2016
Imprint: ISTE Press - Elsevier
Language: English

This book presents a short introduction to continuous-time financial models. An overview of the basics of stochastic analysis precedes a focus on the Black–Scholes and interest rate models. Other topics covered include self-financing strategies, option pricing, exotic options and risk-neutral probabilities. Vasicek, Cox−Ingersoll−Ross, and Heath–Jarrow–Morton interest rate models are also explored. The author presents practitioners with a basic introduction, with more rigorous information provided for mathematicians. The reader is assumed to be familiar with the basics of probability theory. Some basic knowledge of stochastic integration and differential equations theory is preferable, although all preliminary information is given in the first part of the book. Some relatively simple theoretical exercises are also provided.

  • About continuous-time stochastic models of financial mathematics
  • Black-Sholes model and interest rate models
  • Requiring a minimum knowledge of stochastic integration and stochastic differential equations
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This book presents a short introduction to continuous-time financial models. An overview of the basics of stochastic analysis precedes a focus on the Black–Scholes and interest rate models. Other topics covered include self-financing strategies, option pricing, exotic options and risk-neutral probabilities. Vasicek, Cox−Ingersoll−Ross, and Heath–Jarrow–Morton interest rate models are also explored. The author presents practitioners with a basic introduction, with more rigorous information provided for mathematicians. The reader is assumed to be familiar with the basics of probability theory. Some basic knowledge of stochastic integration and differential equations theory is preferable, although all preliminary information is given in the first part of the book. Some relatively simple theoretical exercises are also provided.

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