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Probability for finance /

By: Kopp, P. E, 1944-
Title By: Malczak, Jan | Zastawniak, Tomasz, 1976-
Material type: BookSeries: Mastering mathematical finance.Publisher: Cambridge : Cambridge University Press, 2014.Description: viii, 188 p. : ill ; 24 cm.ISBN: 9781107002494; 1107002494 (hbk.); 9780521175579 (pbk.); 0521175577 (pbk.)Subject(s): Business mathematics | ProbabilitiesDDC classification: 332.01519 Online resources: Location Map
Summary:
A rigorous, unfussy introduction to modern probability theory that focuses squarely on applications in finance.
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.
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Item type Home library Call number Status Date due Barcode Item holds
REGULAR University of Wollongong in Dubai
Main Collection
332.01519 KO PR (Browse shelf) Available T0012548
Total holds: 0

Includes index.

A rigorous, unfussy introduction to modern probability theory that focuses squarely on applications in finance.

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.

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