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Risk control and derivative pricing have become of major concern to financial institutions, and there is a real need for adequate statistical tools to measure and anticipate the amplitude of the potential moves of the financial markets. Summarising theoretical developments in the field, this 2003 second edition has been substantially expanded. Additional chapters now cover stochastic processes, Monte-Carlo methods, Black-Scholes theory, the theory of the yield curve, and Minority Game. There are discussions on aspects of data analysis, financial products, non-linear correlations, and herding, feedback and agent based models. This book has become a classic reference for graduate students and researchers working in econophysics and mathematical finance, and for quantitative analysts working on risk management, derivative pricing and quantitative trading strategies.

339.72 --- 519.2 --- Finance --- Financial engineering --- Risk assessment --- Risk management --- Analysis, Risk --- Assessment, Risk --- Risk analysis --- Risk evaluation --- Computational finance --- Engineering, Financial --- Funding --- Funds --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- 339.72 Internationaal betalingsverkeer. Valutahandel. Wisselmarkten. Deviezenhandel. Internationale kapitaalmarkt. Flow and funds analysis. Betalingsbalans. Internationale geldmarkt. --- Internationaal betalingsverkeer. Valutahandel. Wisselmarkten. Deviezenhandel. Internationale kapitaalmarkt. Flow and funds analysis. Betalingsbalans. Internationale geldmarkt. --- Insurance --- Management --- Evaluation --- Economics --- Currency question --- Internationaal betalingsverkeer. Valutahandel. Wisselmarkten. Deviezenhandel. Internationale kapitaalmarkt. Flow and funds analysis. Betalingsbalans. Internationale geldmarkt --- Capital structure --- 658.155 --- 305.91 --- 333.605 --- 336.312.3 --- 339.4 --- AA / International- internationaal --- Econometrie van de financiële activa. Portfolio allocation en management. CAPM. Bubbles --- Nieuwe financiële instrumenten --- Solvabiliteit, kredietwaardigheid van de landen. Risicolanden --- Vermogensbeheer. Financiële analyse. Verspreiding van de beleggingsrisico's --- Finance. --- Financial engineering. --- Risk assessment. --- Risk management. --- Physics --- General and Others

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Finances --- Valeurs mobilières --- Options (Finances) --- Gestion du risque --- Modèles mathématiques. --- Modèles mathématiques --- Risk management --- Finance --- 658.15 --- Funding --- Funds --- Economics --- Currency question --- Insurance --- Management --- Finances - Gestion du risque - Modèles mathématiques. --- Valeurs mobilières - Modèles mathématiques --- Options (Finances) - Modèles mathématiques --- option --- marché à terme --- risque financier --- probabilités --- FINANCE --- FINANCIAL RISK --- RISK MANAGEMENT --- MATHEMATICAL MODELS

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The real world is perceived and broken down as data, models and algorithms in the eyes of physicists and engineers. Data is noisy by nature and classical statistical tools have so far been successful in dealing with relatively smaller levels of randomness. The recent emergence of Big Data and the required computing power to analyse them have rendered classical tools outdated and insufficient. Tools such as random matrix theory and the study of large sample covariance matrices can efficiently process these big data sets and help make sense of modern, deep learning algorithms. Presenting an introductory calculus course for random matrices, the book focusses on modern concepts in matrix theory, generalising the standard concept of probabilistic independence to non-commuting random variables. Concretely worked out examples and applications to financial engineering and portfolio construction make this unique book an essential tool for physicists, engineers, data analysts, and economists.

Random matrices.

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There has been recently some interdisciplinary convergence on a number of precise topics which can be considered as prototypes of complex systems. This convergence is best appreciated at the level of the techniques needed to deal with these systems, which include: 1) A domain of research around a multiple point where statistical physics, information theory, algorithmic computer science, and more theoretical (probabilistic) computer science meet: this covers some aspects of error correcting codes, stochastic optimization algorithms, typical case complexity and phase transitions, constr

System analysis --- Computational complexity

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We construct a model of an exchange economy in which agents trade assets contingent on an observable signal, the probability of which depends on public opinion. The agents in our model are replaced occasionally and each person updates beliefs in response to observed outcomes. We show that the distribution of the observed signal is described by a quasi-non-ergodic process and that people continue to disagree with each other forever. These disagreements generate large wealth inequalities that arise from the multiplicative nature of wealth dynamics which make successful bold bets highly profitable.