Extended Abstracts Summer 2015

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ISBN/EAN: 9783319517537

This book is divided into two parts, the first of which seeks to connect the phase transitions of various disciplines, including game theory, and to explore the synergies between statistical physics and combinatorics. Phase Transitions has been an active multidisciplinary field of research, bringing together physicists, computer scientists and mathematicians. The main research theme explores how atomic agents that act locally and microscopically lead to discontinuous macroscopic changes. Adopting this perspective has proven to be especially useful in studying the evolution of random and usually complex or large combinatorial objects (like networks or logic formulas) with respect to discontinuous changes in global parameters like connectivity, satisfiability etc. There is, of course, an obvious strategic element in the formation of a transition: the atomic agents 'selfishly' seek to optimize a local parameter. However, up to now this game-theoretic aspect of abrupt, locally triggered changes had not been extensively studied. 

In turn, the book's second part is devoted to mathematical and computational methods applied to the pricing of financial contracts and the measurement of financial risks. The tools and techniques used to tackle these problems cover a wide spectrum of fields, like stochastic calculus, numerical analysis, partial differential equations, statistics and econometrics. Quantitative Finance is a highly active field of research and is increasingly attracting the interest of academics and practitioners alike. The material presented addresses a wide variety of new challenges for this audience. 

Autor: Josep Díaz, Lefteris Kirousis, Luis Ortiz-Gracia, Maria Serna
EAN: 9783319517537
eBook Format: PDF
Sprache: Englisch
Produktart: eBook
Veröffentlichungsdatum: 24.02.2017
Untertitel: Strategic Behavior in Combinatorial Structures; Quantitative Finance
Kategorie:
Schlagworte: Lovatz local lemma Nash equilibria auctions phase transitions random graphs stochastic processes

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