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Credit risk remains one of the major risks faced by most financial and credit institutions. It is deeply connected to the real economy due to the systemic nature of some banks, but also because well-managed lending facilities are key for wealth creation and technological innovation. This book is a collection of innovative papers in the field of credit risk management. Besides the probability of default (PD), the major driver of credit risk is the loss given default (LGD). In spite of its central importance, LGD modeling remains largely unexplored in the academic literature. This book proposes three contributions in the field. Ye & Bellotti exploit a large private dataset featuring non-performing loans to design a beta mixture model. Their model can be used to improve recovery rate forecasts and, therefore, to enhance capital requirement mechanisms. François uses instead the price of defaultable instruments to infer the determinants of market-implied recovery rates and finds that macroeconomic and long-term issuer specific factors are the main determinants of market-implied LGDs. Cheng & Cirillo address the problem of modeling the dependency between PD and LGD using an original, urn-based statistical model. Fadina & Schmidt propose an improvement of intensity-based default models by accounting for ambiguity around both the intensity process and the recovery rate. Another topic deserving more attention is trade credit, which consists of the supplier providing credit facilities to his customers. Whereas this is likely to stimulate exchanges in general, it also magnifies credit risk. This is a difficult problem that remains largely unexplored. Kanapickiene & Spicas propose a simple but yet practical model to assess trade credit risk associated with SMEs and microenterprises operating in Lithuania. Another topical area in credit risk is counterparty risk and all other adjustments (such as liquidity and capital adjustments), known as XVA. Chataignier & Crépey propose a genetic algorithm to compress CVA and to obtain affordable incremental figures. Anagnostou & Kandhai introduce a hidden Markov model to simulate exchange rate scenarios for counterparty risk. Eventually, Boursicot et al. analyzes CoCo bonds, and find that they reduce the total cost of debt, which is positive for shareholders. In a nutshell, all the featured papers contribute to shedding light on various aspects of credit risk management that have, so far, largely remained unexplored.

Coins, banknotes, medals, seals (numismatics) --- recovery rates --- beta regression --- credit risk --- contingent convertible debt --- financial modelling --- risk management --- financial crisis --- recovery rate --- loss given default --- model ambiguity --- default time --- no-arbitrage --- reduced-form HJM models --- recovery process --- Counterparty Credit Risk --- Hidden Markov Model --- Risk Factor Evolution --- Backtesting --- FX rate --- Geometric Brownian Motion --- trade credit --- small and micro-enterprises --- financial non-financial variables --- risk assessment --- logistic regression --- probability of default --- wrong-way risk --- dependence --- urn model --- counterparty risk --- credit valuation adjustment (CVA) --- XVA (X-valuation adjustments) compression --- genetic algorithm --- n/a

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Quantal Response Equilibrium presents a stochastic theory of games that unites probabilistic choice models developed in psychology and statistics with the Nash equilibrium approach of classical game theory. Nash equilibrium assumes precise and perfect decision making in games, but human behavior is inherently stochastic and people realize that the behavior of others is not perfectly predictable. In contrast, QRE models choice behavior as probabilistic and extends classical game theory into a more realistic and useful framework with broad applications for economics, political science, management, and other social sciences.Quantal Response Equilibrium spans the range from basic theoretical foundations to examples of how the principles yield useful predictions and insights in strategic settings, including voting, bargaining, auctions, public goods provision, and more. The approach provides a natural framework for estimating the effects of behavioral factors like altruism, reciprocity, risk aversion, judgment fallacies, and impatience. New theoretical results push the frontiers of models that include heterogeneity, learning, and well-specified behavioral modifications of rational choice and rational expectations. The empirical relevance of the theory is enhanced by discussion of data from controlled laboratory experiments, along with a detailed users' guide for estimation techniques.Quantal Response Equilibrium makes pioneering game-theoretic methods and interdisciplinary applications available to a wide audience.

Game theory. --- AQRE. --- Markov QRE. --- Nash equilibrium. --- QRE reesarch. --- QRE. --- agent quantal response equilibrium. --- altruism. --- applications. --- auctions. --- bargaining. --- binary-choice games. --- choice distribution. --- classical game theory. --- dynamic quantal response equilibrium. --- dynamics. --- economics. --- estimation. --- extensive-form games. --- game theory. --- games. --- impatience. --- imperfectly rational behavior. --- inequity aversion. --- learning models. --- logit QRE. --- logit equilibrium. --- maximum-likelihood methods. --- methodology. --- minimum-effort coordination game. --- noisy behavior. --- noisy introspection. --- normal-form games. --- participation games. --- player skills. --- political science. --- price-competition game. --- probabilistic choice. --- pure game theory. --- quantal response equilibrium. --- reciprocity. --- reduced-form approach. --- rent dissipation. --- risk aversion. --- skill heterogeneity. --- social science. --- statistical game theory. --- symmetric game. --- theory of games. --- theory.

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The last decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results. The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.

519.246 --- Time-series analysis --- modeles economiques --- AA / International- internationaal --- 303.0 --- 304.0 --- 306.5 --- 519.55 --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Statistics of stochastic processes. Estimation of stochastic processes. Hypothesis testing. Statistics of point processes. Time series analysis. Auto-correlation. Regression --- economische modellen --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Statistische analyse (methodologie). --- 519.246 Statistics of stochastic processes. Estimation of stochastic processes. Hypothesis testing. Statistics of point processes. Time series analysis. Auto-correlation. Regression --- Time-series analysis. --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen --- Statistische analyse (methodologie) --- Stochastic processes --- Statistical science --- Série chronologique --- Absolute summability. --- Autocovariance. --- Bartlett kernel. --- Block exogeneity. --- Cointegrating vector. --- Consumption spending. --- Cospectrum. --- Dickey-Fuller test. --- EM algorithm. --- Exchange rates. --- Filters. --- Fundamental innovation. --- Gamma distribution. --- Global identification. --- Gross national product. --- Hessian matrix. --- Inequality constraints. --- Invertibility. --- Jacobian matrix. --- Joint density. --- Khinchine's theorem. --- Kronecker product. --- Lagrange multiplier. --- Loss function. --- Mean-value theorem. --- Mixingales. --- Monte Carlo method. --- Newton-Raphson. --- Order in probability. --- Orthogonal. --- Permanent income. --- Quadrature spectrum. --- Recessions. --- Reduced form. --- Sample periodogram. --- Stock prices. --- Taylor series. --- Vech operator. --- Time series analysis