Provides a foundation for probability based on game theory rather than measure theory.
* A strong philosophical approach with practical applications.
* Presents in-depth coverage of classical probability theory as well as new theory.
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GLENN SHAFER, PhD, is Professor in the Graduate School of Management at Rutgers University. He is also the author of The Art of Causal Conjecture, Probabilistic Expert Systems, and A Mathematical Theory of Evidence.
VLADIMIR VOVK, PhD, is Professor in the Department of Computer Science at Royal Holloway, University of London.
A new game-theoretic approach to probability and finance
Probability and Finance presents essential reading for anyone whostudies or uses probability. Mathematicians and statisticians willfind in it a new framework for probability: game theory instead ofmeasure theory. Philosophers will find a surpising synthesis of theobjective and the subjective. Practitioners, especially infinancial engineering, will learn new ways to understand andsometimes eliminate stochastic models.
The first half of the book explains a new mathematical andphilosophical framework for probability, based on a sequential gamebetween an idealized scientist and the world. Two very accessibleintroductory chapters, one presenting an overview of the newframework and one reviewing its historical context, are followed bya careful mathematical treatment of probability's classical limittheorems.
The second half of the book, on finance, illustrates the potentialof the new framework. It proposes greater use of the market andless use of stochastic models in the pricing of financialderivatives, and it shows how purely game-theoretic probability canreplace stochastic models in the efficient-market hypothesis.
A new game-theoretic approach to probability and finance
Probability and Finance presents essential reading for anyone who studies or uses probability. Mathematicians and statisticians will find in it a new framework for probability: game theory instead of measure theory. Philosophers will find a surpising synthesis of the objective and the subjective. Practitioners, especially in financial engineering, will learn new ways to understand and sometimes eliminate stochastic models.
The first half of the book explains a new mathematical and philosophical framework for probability, based on a sequential game between an idealized scientist and the world. Two very accessible introductory chapters, one presenting an overview of the new framework and one reviewing its historical context, are followed by a careful mathematical treatment of probability's classical limit theorems.
The second half of the book, on finance, illustrates the potential of the new framework. It proposes greater use of the market and less use of stochastic models in the pricing of financial derivatives, and it shows how purely game-theoretic probability can replace stochastic models in the efficient-market hypothesis.
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