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Books > Business & Economics > Finance & accounting
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The Interval Market Model in Mathematical Finance - Game-Theoretic Methods (Paperback, 2013 ed.)
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The Interval Market Model in Mathematical Finance - Game-Theoretic Methods (Paperback, 2013 ed.)
Series: Static & Dynamic Game Theory: Foundations & Applications
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Toward the late 1990s, several research groups independently began
developing new, related theories in mathematical finance. These
theories did away with the standard stochastic geometric diffusion
"Samuelson" market model (also known as the Black-Scholes model
because it is used in that most famous theory), instead opting for
models that allowed minimax approaches to complement or replace
stochastic methods. Among the most fruitful models were those
utilizing game-theoretic tools and the so-called interval market
model. Over time, these models have slowly but steadily gained
influence in the financial community, providing a useful
alternative to classical methods. A self-contained monograph, The
Interval Market Model in Mathematical Finance: Game-Theoretic
Methods assembles some of the most important results, old and new,
in this area of research. Written by seven of the most prominent
pioneers of the interval market model and game-theoretic finance,
the work provides a detailed account of several closely related
modeling techniques for an array of problems in mathematical
economics. The book is divided into five parts, which successively
address topics including: * probability-free Black-Scholes theory;
* fair-price interval of an option; * representation formulas and
fast algorithms for option pricing; * rainbow options; * tychastic
approach of mathematical finance based upon viability theory. This
book provides a welcome addition to the literature, complementing
myriad titles on the market that take a classical approach to
mathematical finance. It is a worthwhile resource for researchers
in applied mathematics and quantitative finance, and has also been
written in a manner accessible to financially-inclined readers with
a limited technical background.
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