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Investments --- Statistical decision. --- Financial engineering. --- Investissements --- Prise de décision (Statistique) --- Ingénierie financière --- Mathematics. --- Mathématiques

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Game-theoretic probability and finance come of age Glenn Shafer and Vladimir Vovk’s Probability and Finance , published in 2001, showed that perfect-information games can be used to define mathematical probability. Based on fifteen years of further research, Game-Theoretic Foundations for Probability and Finance presents a mature view of the foundational role game theory can play. Its account of probability theory opens the way to new methods of prediction and testing and makes many statistical methods more transparent and widely usable. Its contributions to finance theory include purely game-theoretic accounts of Ito’s stochastic calculus, the capital asset pricing model, the equity premium, and portfolio theory. Game-Theoretic Foundations for Probability and Finance is a book of research. It is also a teaching resource. Each chapter is supplemented with carefully designed exercises and notes relating the new theory to its historical context. Praise from early readers “Ever since Kolmogorov's Grundbegriffe , the standard mathematical treatment of probability theory has been measure-theoretic. In this ground-breaking work, Shafer and Vovk give a game-theoretic foundation instead. While being just as rigorous, the game-theoretic approach allows for vast and useful generalizations of classical measure-theoretic results, while also giving rise to new, radical ideas for prediction, statistics and mathematical finance without stochastic assumptions. The authors set out their theory in great detail, resulting in what is definitely one of the most important books on the foundations of probability to have appeared in the last few decades.” – Peter Grünwald, CWI and University of Leiden “Shafer and Vovk have thoroughly re-written their 2001 book on the game-theoretic foundations for probability and for finance. They have included an account of the tremendous growth that has occurred since, in the game-theoretic and pathwise approaches to stochastic analysis and in their applications to continuous-time finance. This new book will undoubtedly spur a better understanding of the foundations of these very important fields, and we should all be grateful to its authors.” – Ioannis Karatzas, Columbia University

Finance --- Game theory. --- Statistical methods. --- Mathematical models. --- E-books

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This book constitutes the refereed proceedings of the Third International Symposium on Statistical Learning and Data Sciences, SLDS 2015, held in Egham, Surrey, UK, April 2015. The 36 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 59 submissions. The papers are organized in topical sections on statistical learning and its applications, conformal prediction and its applications, new frontiers in data analysis for nuclear fusion, and geometric data analysis.

Computer Science. --- Artificial Intelligence (incl. Robotics). --- Algorithm Analysis and Problem Complexity. --- Information Systems Applications (incl. Internet). --- Database Management. --- Computation by Abstract Devices. --- Information Storage and Retrieval. --- Computer science. --- Computer software. --- Database management. --- Information storage and retrieval systems. --- Artificial intelligence. --- Informatique --- Logiciels --- Bases de données --- Systèmes d'information --- Intelligence artificielle --- Gestion --- Mechanical Engineering --- Engineering & Applied Sciences --- Computer Science --- Mechanical Engineering - General --- Computers. --- Algorithms. --- Information storage and retrieval. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Algorism --- Algebra --- Arithmetic --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Informatics --- Science --- Foundations --- Information storage and retrieva. --- Artificial Intelligence. --- Software, Computer --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Machine learning. --- Learning, Machine --- Artificial intelligence

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This book brings together historical notes, reviews of research developments, fresh ideas on how to make VC (Vapnik–Chervonenkis) guarantees tighter, and new technical contributions in the areas of machine learning, statistical inference, classification, algorithmic statistics, and pattern recognition. The contributors are leading scientists in domains such as statistics, mathematics, and theoretical computer science, and the book will be of interest to researchers and graduate students in these domains.

Computer Science --- Mechanical Engineering - General --- Engineering & Applied Sciences --- Mechanical Engineering --- Machine learning. --- Pattern recognition systems. --- Pattern classification systems --- Pattern recognition computers --- Learning, Machine --- Computer science. --- Mathematical statistics. --- Artificial intelligence. --- Mathematical optimization. --- Statistics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Statistical Theory and Methods. --- Probability and Statistics in Computer Science. --- Optimization. --- Pattern perception --- Computer vision --- Artificial intelligence --- Machine theory --- Artificial Intelligence. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Informatics --- Science --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Self-organizing systems --- Fifth generation computers --- Neural computers --- Statistical methods --- Statistics . --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics

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Computer science --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- cryptologie --- informatica --- statistiek --- programmatielogica --- KI (kunstmatige intelligentie) --- robots --- AI (artificiële intelligentie)