06016nam 2200829Ia 450 991081177420332120240612172200.01-119-97711-81-119-20586-71-283-40512-197866134051281-119-97710-X(CKB)2550000000064895(EBL)699340(OCoLC)760884478(SSID)ssj0000648807(PQKBManifestationID)12295967(PQKBTitleCode)TC0000648807(PQKBWorkID)10600951(PQKB)10878834(MiAaPQ)EBC699340(Au-PeEL)EBL699340(CaPaEBR)ebr10510640(CaONFJC)MIL340512(EXLCZ)99255000000006489520120816d2011 uy 0engur|n|---|||||txtccrFinancial risk forecasting the theory and practice of forecasting market risk, with implementation in R and Matlab /Jón Daníelsson1st ed.Chichester, West Sussex, U.K. Wiley20111 online resource (298 p.)Wiley finance seriesDescription based upon print version of record.0-470-66943-8 Includes bibliographical references (p. [255]-258) and index.Financial Risk Forecasting; Contents; Preface; Acknowledgments; Abbreviations; Notation; 1 Financial markets, prices and risk; 1.1 Prices, returns and stock indices; 1.1.1 Stock indices; 1.1.2 Prices and returns; 1.2 S&P 500 returns; 1.2.1 S&P 500 statistics; 1.2.2 S&P 500 statistics in R and Matlab; 1.3 The stylized facts of financial returns; 1.4 Volatility; 1.4.1 Volatility clusters; 1.4.2 Volatility clusters and the ACF; 1.5 Nonnormality and fat tails; 1.6 Identification of fat tails; 1.6.1 Statistical tests for fat tails; 1.6.2 Graphical methods for fat tail analysis1.6.3 Implications of fat tails in finance1.7 Nonlinear dependence; 1.7.1 Sample evidence of nonlinear dependence; 1.7.2 Exceedance correlations; 1.8 Copulas; 1.8.1 The Gaussian copula; 1.8.2 The theory of copulas; 1.8.3 An application of copulas; 1.8.4 Some challenges in using copulas; 1.9 Summary; 2 Univariate volatility modeling; 2.1 Modeling volatility; 2.2 Simple volatility models; 2.2.1 Moving average models; 2.2.2 EWMA model; 2.3 GARCH and conditional volatility; 2.3.1 ARCH; 2.3.2 GARCH; 2.3.3 The ''memory'' of a GARCH model; 2.3.4 Normal GARCH; 2.3.5 Student-t GARCH2.3.6 (G)ARCH in mean2.4 Maximum likelihood estimation of volatility models; 2.4.1 The ARCH(1) likelihood function; 2.4.2 The GARCH(1,1) likelihood function; 2.4.3 On the importance of σ1; 2.4.4 Issues in estimation; 2.5 Diagnosing volatility models; 2.5.1 Likelihood ratio tests and parameter significance; 2.5.2 Analysis of model residuals; 2.5.3 Statistical goodness-of-fit measures; 2.6 Application of ARCH and GARCH; 2.6.1 Estimation results; 2.6.2 Likelihood ratio tests; 2.6.3 Residual analysis; 2.6.4 Graphical analysis; 2.6.5 Implementation; 2.7 Other GARCH-type models2.7.1 Leverage effects and asymmetry2.7.2 Power models; 2.7.3 APARCH; 2.7.4 Application of APARCH models; 2.7.5 Estimation of APARCH; 2.8 Alternative volatility models; 2.8.1 Implied volatility; 2.8.2 Realized volatility; 2.8.3 Stochastic volatility; 2.9 Summary; 3 Multivariate volatility models; 3.1 Multivariate volatility forecasting; 3.1.1 Application; 3.2 EWMA; 3.3 Orthogonal GARCH; 3.3.1 Orthogonalizing covariance; 3.3.2 Implementation; 3.3.3 Large-scale implementations; 3.4 CCC and DCC models; 3.4.1 Constant conditional correlations (CCC); 3.4.2 Dynamic conditional correlations (DCC)3.4.3 Implementation3.5 Estimation comparison; 3.6 Multivariate extensions of GARCH; 3.6.1 Numerical problems; 3.6.2 The BEKK model; 3.7 Summary; 4 Risk measures; 4.1 Defining and measuring risk; 4.2 Volatility; 4.3 Value-at-risk; 4.3.1 Is VaR a negative or positive number?; 4.3.2 The three steps in VaR calculations; 4.3.3 Interpreting and analyzing VaR; 4.3.4 VaR and normality; 4.3.5 Sign of VaR; 4.4 Issues in applying VaR; 4.4.1 VaR is only a quantile; 4.4.2 Coherence; 4.4.3 Does VaR really violate subadditivity?; 4.4.4 Manipulating VaR; 4.5 Expected shortfall4.6 Holding periods, scaling and the square root of timeFinancial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques. Written by renowned risk expert Jon Danielsson, the book begins with an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It then goes oWiley finance series.Financial risk managementForecastingFinancial risk managementSimulation methodsR (Computer program language)Gestió financerathubGestió del riscthubPrevisióthubMètodes de simulacióthubLlibres electrònicsthubFinancial risk managementForecasting.Financial risk managementSimulation methods.R (Computer program language).Gestió financeraGestió del riscPrevisióMètodes de simulació658.155658.1550112Daníelsson Jón375914MiAaPQMiAaPQMiAaPQBOOK9910811774203321Financial risk forecasting1136804UNINA