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Financial risk forecasting [[electronic resource] ] : the theory and practice of forecasting market risk, with implementation in R and Matlab / / Jón Daníelsson
Financial risk forecasting [[electronic resource] ] : the theory and practice of forecasting market risk, with implementation in R and Matlab / / Jón Daníelsson
Autore Daníelsson Jón
Pubbl/distr/stampa Chichester, West Sussex, U.K., : Wiley, 2011
Descrizione fisica 1 online resource (298 p.)
Disciplina 658.155
658.1550112
Collana Wiley finance series
Soggetto topico Financial risk management - Forecasting
Financial risk management - Simulation methods
R (Computer program language)
Gestió financera
Gestió del risc
Previsió
Mètodes de simulació
Soggetto genere / forma Llibres electrònics
ISBN 1-119-97711-8
1-119-20586-7
1-283-40512-1
9786613405128
1-119-97710-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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 analysis
1.6.3 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 GARCH
2.3.6 (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 models
2.7.1 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 shortfall
4.6 Holding periods, scaling and the square root of time
Record Nr. UNINA-9910139552503321
Daníelsson Jón  
Chichester, West Sussex, U.K., : Wiley, 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Financial risk forecasting : the theory and practice of forecasting market risk, with implementation in R and Matlab / / Jón Daníelsson
Financial risk forecasting : the theory and practice of forecasting market risk, with implementation in R and Matlab / / Jón Daníelsson
Autore Daníelsson Jón
Edizione [1st ed.]
Pubbl/distr/stampa Chichester, West Sussex, U.K., : Wiley, 2011
Descrizione fisica 1 online resource (298 p.)
Disciplina 658.155
658.1550112
Collana Wiley finance series
Soggetto topico Financial risk management - Forecasting
Financial risk management - Simulation methods
R (Computer program language)
Gestió financera
Gestió del risc
Previsió
Mètodes de simulació
Soggetto genere / forma Llibres electrònics
ISBN 1-119-97711-8
1-119-20586-7
1-283-40512-1
9786613405128
1-119-97710-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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 analysis
1.6.3 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 GARCH
2.3.6 (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 models
2.7.1 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 shortfall
4.6 Holding periods, scaling and the square root of time
Record Nr. UNINA-9910811774203321
Daníelsson Jón  
Chichester, West Sussex, U.K., : Wiley, 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Wealth Creation in the World’s Largest Mergers and Acquisitions [[electronic resource] ] : Integrated Case Studies / / by B. Rajesh Kumar
Wealth Creation in the World’s Largest Mergers and Acquisitions [[electronic resource] ] : Integrated Case Studies / / by B. Rajesh Kumar
Autore Kumar B. Rajesh
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (xii, 359 pages)
Disciplina 658.15
Collana Management for Professionals
Soggetto topico Business enterprises - Finance
Corporations - Finance
Personal finance
Pensions
Business Finance
Corporate Finance
Personal Finance/Wealth Management/Pension Planning
Fusió d'empreses
Adquisició d'empreses
Rendibilitat
Gestió financera
Estudi de casos
Soggetto genere / forma Llibres electrònics
ISBN 3-030-02363-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1. Theoretical Perspectives on Mergers and Acquisitions -- Chapter 2. Vodafone Acquisition of Mannesmann -- Chapter 3. American Online -Time Warner Merger and other restructuring -- Chapter 4. Acquisitions by Verizon,- Chapter 5. Dow DuPont Merger -- Chapter 6. Mergers and Acquisitions by Anheuser Busch InBev -- Chapter 7. Merger of Kraft and Heinz Company -- Chapter 8. Acquisitions by Pfizer -- Chapter 9. Exxon Mobil Merger -- Chapter 10. Citicorp -Travelers Group Merger -- Chapter 11. AT&T -Time Warner Acquisition -- Chapter 12. ABN AMRO Acquisition by RFS holding -- Chapter 13. Glaxo SmithKline Merger -- Chapter 14. Acquisitions by Royal Dutch Shell -- Chapter 15. Bell South Merger with AT&T -- Chapter 16. Comcast acquisition of AT&T Broadband -- Chapter 17. Key Mergers of J P Morgan Chase -- Chapter 18. Charter Communication acquisition of Time Warner Cable -- Chapter 19. Actavis-Allergan Merger Deal -- Chapter 20. Dell’s Acquisition of EMC -- Chapter 21. Altria Group’s spin off of Philip Morris International Inc -- Chapter 22. Vodafone Air Touch Merger -- Chapter 23. Bell Atlantic- GTE Merger -- Chapter 24. British Petroleum merger with Amoco -- Chapter 25. Qwest merger with US West -- Chapter 26. WorldCom’s Acquisition of MCI -- Chapter 27. Microsoft’s acquisition of LinkedIn -- Chapter 28. Procter &Gamble’s Acquisition of Gillette -- Chapter 29. Oracle’s hostile takeover of PeopleSoft -- Chapter 30. Mergers and Acquisitions by Bank of America -- Chapter 31. Gaze de Franc Merger with Suez -- Chapter 32. Sanofi-Aventis Merger -- Chapter 33. Bayer’s Acquisition of Monsanto -- Chapter 34. Roche Holding’s acquisition of Genentech -- Chapter 35. France Telecom SA–Orange PLC Merger -- Chapter 36. Merck–Schering Plough Corp Merger -- Chapter 37. Astra-Zeneca Merger -- Chapter 38. HP Compaq Merger -- Chapter 39. Major Acquisitions by Facebook -- Chapter 40. JDS Uniphase Corp and SDL Inc. Merger -- Chapter 41. KKR’s acquisition of First Data -- Chapter 42. Lucent Technologies Acquisition of Ascend Communications -- Chapter 43. Vivendi Seagram Deal -- Chapter 44. Daimler Chrysler Merger -- Chapter 45. Arcelor Mittal Merger.
Record Nr. UNINA-9910337810303321
Kumar B. Rajesh  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui