Description

Book Synopsis
Students and instructors alike will benefit from this rigorous, unfussy text, which keeps a clear focus on the basic probabilistic concepts required for an understanding of financial market models, including independence and conditioning. Assuming only some calculus and linear algebra, the text develops key results of measure and integration, which are applied to probability spaces and random variables, culminating in central limit theory. Consequently it provides essential prerequisites to graduate-level study of modern finance and, more generally, to the study of stochastic processes. Results are proved carefully and the key concepts are motivated by concrete examples drawn from financial market models. Students can test their understanding through the large number of exercises and worked examples that are integral to the text.

Table of Contents
Preface; 1. Probability space; 2. Probability distributions and random variables; 3. Product measure and independence; 4. Conditional expectation; 5. Sequences of random variables; Index.

Probability for Finance

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    £37.37

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    Order before 4pm today for delivery by Fri 26 Jun 2026.

    A Paperback by Ekkehard Kopp, Jan Malczak, Tomasz Zastawniak

    15 in stock


      View other formats and editions of Probability for Finance by Ekkehard Kopp

      Publisher: Cambridge University Press
      Publication Date: 11/21/2013 12:00:00 AM
      ISBN13: 9780521175579, 978-0521175579
      ISBN10: 0521175577

      Description

      Book Synopsis
      Students and instructors alike will benefit from this rigorous, unfussy text, which keeps a clear focus on the basic probabilistic concepts required for an understanding of financial market models, including independence and conditioning. Assuming only some calculus and linear algebra, the text develops key results of measure and integration, which are applied to probability spaces and random variables, culminating in central limit theory. Consequently it provides essential prerequisites to graduate-level study of modern finance and, more generally, to the study of stochastic processes. Results are proved carefully and the key concepts are motivated by concrete examples drawn from financial market models. Students can test their understanding through the large number of exercises and worked examples that are integral to the text.

      Table of Contents
      Preface; 1. Probability space; 2. Probability distributions and random variables; 3. Product measure and independence; 4. Conditional expectation; 5. Sequences of random variables; Index.

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