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Derivative securities --- Risk management --- Investment analysis --- Mathematical models. --- Derivative securities - Mathematical models. --- Risk management - Mathematical models. --- Investment analysis - Mathematical models. --- Gestion du risque

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The main theme of this volume is credit risk and credit derivatives. Recent developments in financial markets show that appropriate modeling and quantification of credit risk is fundamental in the context of modern complex structured financial products. The reader will find several points of view on credit risk when looked at from the perspective of Econometrics and Financial Mathematics. The volume consists of eleven contributions by both practitioners and theoreticians with expertise in financial markets, in general, and econometrics and mathematical finance in particular. The challenge of modeling defaults and their correlations is addressed, and new results on copula, reduced form and structural models, and the top-down approach are presented. After the so-called subprime crisis that hit global markets in the summer of 2007, the volume is very timely and will be useful to researchers in the area of credit risk.

Credit -- Mathematical models. --- Credit derivatives -- Mathematical models. --- Risk management -- Mathematical models. --- Credit derivatives --- Credit --- Econometrics --- Risk management --- Insurance --- Management --- Borrowing --- Finance --- Money --- Loans --- Derivative securities --- Mathematical models --- Quantitative methods (economics) --- International financial management --- Business & Economics --- Econometrics. --- Forecasting. --- Economics, Mathematical --- Statistics

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This book provides a comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management and equips readers - whether financial risk analysts, actuaries, regulators, or students of quantitative finance - with practical tools to solve real-world problems.

Private finance --- International financial management --- Actuarial mathematics --- Risk management --- Finance --- Insurance --- Mathematical statistics --- Mathematical models --- MATHEMATICAL MODELS -- 658.30 --- Mathematical statistics. --- Gestion du risque --- Finances --- Assurance --- Statistique mathématique --- Mathematical models. --- Modèles mathématiques. --- Risk management - Mathematical models --- Finance - Mathematical models --- Insurance - Mathematical models --- Statistique mathématique --- Modèles mathématiques.

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Financial markets respond to information virtually instantaneously. Each new piece of information influences the prices of assets and their correlations with each other, and as the system rapidly changes, so too do correlation forecasts. This fast-evolving environment presents econometricians with the challenge of forecasting dynamic correlations, which are essential inputs to risk measurement, portfolio allocation, derivative pricing, and many other critical financial activities. In Anticipating Correlations, Nobel Prize-winning economist Robert Engle introduces an important new method for estimating correlations for large systems of assets: Dynamic Conditional Correlation (DCC). Engle demonstrates the role of correlations in financial decision making, and addresses the economic underpinnings and theoretical properties of correlations and their relation to other measures of dependence. He compares DCC with other correlation estimators such as historical correlation, exponential smoothing, and multivariate GARCH, and he presents a range of important applications of DCC. Engle presents the asymmetric model and illustrates it using a multicountry equity and bond return model. He introduces the new FACTOR DCC model that blends factor models with the DCC to produce a model with the best features of both, and illustrates it using an array of U.S. large-cap equities. Engle shows how overinvestment in collateralized debt obligations, or CDOs, lies at the heart of the subprime mortgage crisis--and how the correlation models in this book could have foreseen the risks. A technical chapter of econometric results also is included. Based on the Econometric and Tinbergen Institutes Lectures, Anticipating Correlations puts powerful new forecasting tools into the hands of researchers, financial analysts, risk managers, derivative quants, and graduate students.

Correlation (Statistics). --- Economic forecasting --Mathematical models. --- Finance --Econometrics models. --- Risk management --Mathematical models. --- Finance --- Risk management --- Economic forecasting --- Correlation (Statistics) --- Business & Economics --- Finance - General --- Investment & Speculation --- Econometric models --- Mathematical models --- Econometric models. --- Mathematical models. --- Funding --- Funds --- Economics --- Currency question --- Least squares --- Mathematical statistics --- Probabilities --- Regression analysis --- Statistics --- Instrumental variables (Statistics) --- Econometrics models. --- Graphic methods

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"Preface Second Edition The first edition of this book appeared eight years ago. Since then the banking industry experienced a lot of change and challenges. The most recent financial crisis which started around May 2007 and lasted in its core period until early 2009 gave rise for a lot of scepticism whether credit risk models are appropriate to capture the true nature of risks inherent in credit portfolios in general and structured credit products in particular. In a recent article two of us discuss common credit risk modeling approaches in the light of the most recent crisis and invite readers to participate in the discussion; see [25]. A key observation in a discussion like the one in [25] is that the universe of available models and tools is sufficiently rich for doing a good job even in a severe crisis scenario as banks recently experienced it. What seems to be more critical is an appropriate model choice, parameterization of models, dealing with uncertainties, e.g., based on insufficient data, and communication of model outcomes to decision makers and executive senior management. These are the four main areas of challenge where we think that a lot of work and rethinking needs to be done in a p︠ost-crisis ̕reflection of credit risk models. In the first edition of this book we focussed on the description of common mathematical approaches to model credit portfolios. We did not change this philosophy for the second edition. Therefore, we left large parts of the book unchanged in its core message but supplemented the exposition with new model developments and with details we omitted in the first edition"--

Credit --- Risk management --- Management --- Mathematical models --- 658.880151 --- 305.7 --- 333.109 --- 333.70 --- AA / International- internationaal --- Borrowing --- Finance --- Money --- Loans --- Management&delete& --- Econometrie van het gedrag van de financiële tussenpersonen. Monetaire econometrische modellen. Monetaire agregaten. vraag voor geld. Krediet. Rente --- Veiligheid. Bankovervallen. Bankrisico's --- Theorie en organisatie van het bankkrediet --- Credit - Management - Mathematical models --- Risk management - Mathematical models