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  • af Kevin J. Hastings
    644,95 kr.

    Introduction to Financial Mathematics motivates students through a discussion of personal finances and portfolio management. The book covers nearly all of the syllabus topics of the Financial Mathematics Actuarial examination to provide students with the foundation they require for future studies and in their careers. It begins

  • af Kevin J. Hastings
    1.002,95 kr.

    This book is a study of the mathematical ideas and techniques that are important to the two main arms of the area of Financial Mathematics: portfolio optimization and derivative valuation. The text is authored for courses taken by advanced undergraduates, MBA, or other students in quantitative finance programs.

  • af Kevin J. Hastings
    1.263,95 kr.

    Introduction to Financial Mathematics motivates students through a discussion of personal finances and portfolio management. The book covers nearly all of the syllabus topics of the Financial Mathematics Actuarial examination to provide students with the foundation they require for future studies and in their careers. It begins by covering standard material on the mathematics of interest and goes on to address probabilistic financial models and the valuation of financial derivatives. Many of the examples in the book involve numerical solution of complicated non-linear equations; others ask students to produce algorithms which beg to be implemented as programs.

  • af Kevin J. Hastings
    756,95 - 2.258,95 kr.

    Focuses on the topics of graph theory, linear programming, stochastic processes, and dynamic programming. Integrating technology into the development, this title features a CD-ROM with Mathematica program. It offers material in areas such as simulation, Brownian motion, and famous graph theory problems such as the traveling salesman problem.

  • af Kevin J. Hastings
    842,95 - 2.258,95 kr.

    Shows you how to create simulations from templates and solve problems using Mathematica. Along with sections on order statistics, transformations of multivariate normal random variables, and Brownian motion, this title offers a section on Markov chains, example data of the normal distribution, focusing on conditional expectation.