LEADER 06208nam 22007332 450 001 9910786998703321 005 20151005020622.0 010 $a1-107-32712-1 010 $a1-107-33688-0 010 $a1-107-33356-3 010 $a1-107-33522-1 010 $a1-139-54093-9 035 $a(CKB)2670000000356624 035 $a(EBL)1139620 035 $a(SSID)ssj0000859926 035 $a(PQKBManifestationID)11503654 035 $a(PQKBTitleCode)TC0000859926 035 $a(PQKBWorkID)10895324 035 $a(PQKB)10584116 035 $a(UkCbUP)CR9781139540933 035 $a(MiAaPQ)EBC1139620 035 $a(Au-PeEL)EBL1139620 035 $a(CaPaEBR)ebr10752974 035 $a(CaONFJC)MIL515093 035 $a(OCoLC)857489673 035 $a(PPN)261294342 035 $a(EXLCZ)992670000000356624 100 $a20120627d2013|||| uy| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDynamic models for volatility and heavy tails $ewith applications to financial and economic time series /$fAndrew C. Harvey$b[electronic resource] 210 1$aCambridge :$cCambridge University Press,$d2013. 215 $a1 online resource (xviii, 261 pages) $cdigital, PDF file(s) 225 1 $aEconometric Society monographs ;$v52 300 $aTitle from publisher's bibliographic system (viewed on 05 Oct 2015). 311 $a1-107-63002-9 311 $a1-107-03472-8 320 $aIncludes bibliographical references (p. 247-254) and indexes. 327 $aContents; Preface; Acronyms and Abbreviations; 1 Introduction; 1.1 Unobserved Components and Filters; 1.2 Independence, White Noise and Martingale Differences; 1.2.1 The Law of Iterated Expectations and Optimal Predictions; 1.2.2 Definitions and Properties; 1.3 Volatility; 1.3.1 Stochastic Volatility; 1.3.2 Generalized Autoregressive Conditional Heteroscedasticity; 1.3.3 Exponential GARCH; 1.3.4 Variance, Scale and Outliers; 1.3.5 Location/Scale Models; 1.4 Dynamic Conditional Score Models; 1.5 Distributions and Quantiles; 1.6 Plan of Book; 2 Statistical Distributions and Asymptotic Theory 327 $a2.1 Distributions2.1.1 Student's t Distribution; 2.1.2 General Error Distribution; 2.1.3 Beta Distribution; 2.1.4 Gamma Distribution; 2.2 Maximum Likelihood; 2.2.1 Student's t Distribution; 2.2.2 General Error Distribution; 2.2.3 Gamma Distribution; 2.2.4 Consistency and Asymptotic Normality*; 2.3 Maximum Likelihood Estimation; 2.3.1 An Information Matrix Lemma; 2.3.2 Information Matrix for the First-Order Model; 2.3.3 Information Matrix with the 0=x""010E Parameterization*; 2.3.4 Asymptotic Distribution; 2.3.5 Consistency and Asymptotic Normality*; 2.3.6 Nonstationarity 327 $a2.3.7 Several Parameters2.4 Higher Order Models; 2.5 Tests; 2.5.1 Serial Correlation; 2.5.2 Goodness of Fit of Distributions; 2.5.3 Residuals; 2.5.4 Model Fit; 2.6 Explanatory Variables; 3 Location; 3.1 Dynamic Student's t Location Model; 3.2 Basic Properties; 3.2.1 Generalization and Reduced Form; 3.2.2 Moments of the Observations; 3.2.3 Autocorrelation Function; 3.3 Maximum Likelihood Estimation; 3.3.1 Asymptotic Distribution of the Maximum Likelihood Estimator; 3.3.2 Monte Carlo Experiments; 3.3.3 Application to U.S. GDP; 3.4 Parameter Restrictions* 327 $a3.5 Higher Order Models and the State Space Form*3.5.1 Linear Gaussian Models and the Kalman Filter; 3.5.2 The DCS Model; 3.5.3 QARMA Models; 3.6 Trend and Seasonality; 3.6.1 Local Level Model; 3.6.2 Application to Weekly Hours of Employees in U.S. Manufacturing; 3.6.3 Local Linear Trend; 3.6.4 Stochastic Seasonal; 3.6.5 Application to Rail Travel; 3.6.6 QARIMA and Seasonal QARIMA Models*; 3.7 Smoothing; 3.7.1 Weights; 3.7.2 Smoothing Recursions for Linear State Space Models; 3.7.3 Smoothing Recursions for DCS Models; 3.7.4 Conditional Mode Estimation and the Score; 3.8 Forecasting 327 $a3.8.1 QARMA Models3.8.2 State Space Form*; 3.9 Components and Long Memory; 3.10 General Error Distribution; 3.11 Skew Distributions; 3.11.1 How to Skew a Distribution; 3.11.2 Dynamic Skew-t Location Model; 4 Scale; 4.1 Beta-tttt-EGARCH; 4.2 Properties of Stationary Beta-tttt-EGARCH Models; 4.2.1 Exponential GARCH; 4.2.2 Moments; 4.2.3 Autocorrelation Functions of Squares and Powersof Absolute Values; 4.2.4 Autocorrelations and Kurtosis; 4.3 Leverage Effects; 4.4 Gamma-GED-EGARCH; 4.5 Forecasting; 4.5.1 Beta-t-EGARCH; 4.5.2 Gamma-GED-EGARCH; 4.5.3 Integrated Exponential Models 327 $a4.5.4 Predictive Distribution 330 $aThe volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey's new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling. 410 0$aEconometric Society monographs ;$v52. 517 3 $aDynamic Models for Volatility & Heavy Tails 606 $aEconometrics 606 $aFinance$xMathematical models 606 $aTime-series analysis 615 0$aEconometrics. 615 0$aFinance$xMathematical models. 615 0$aTime-series analysis. 676 $a330.01/5195 700 $aHarvey$b A. C$g(Andrew C.),$0982067 801 0$bUkCbUP 801 1$bUkCbUP 906 $aBOOK 912 $a9910786998703321 996 $aDynamic models for volatility and heavy tails$93688690 997 $aUNINA LEADER 05800oam 22007575 450 001 9910791321903321 005 20230126203904.0 010 $a1-4648-0102-9 024 7 $a10.1596/978-1-4648-0101-3 035 $a(CKB)2550000001202941 035 $a(EBL)1611994 035 $a(SSID)ssj0001084499 035 $a(PQKBManifestationID)11587174 035 $a(PQKBTitleCode)TC0001084499 035 $a(PQKBWorkID)11036284 035 $a(PQKB)11093036 035 $a(MiAaPQ)EBC1611994 035 $a(DLC) 2013042860 035 $a(Au-PeEL)EBL1611994 035 $a(CaPaEBR)ebr10827230 035 $a(CaONFJC)MIL572407 035 $a(OCoLC)861744939 035 $a(The World Bank)17913316 035 $a(US-djbf)17913316 035 $a(EXLCZ)992550000001202941 100 $a20131022d2014 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aHow firms cope with crime and violence $eexperiences from around the world /$fMichael Goldberg, Kwang W. Kim, and Maria Ariani 210 1$aWashington, DC :$cThe World Bank,$d[2014] 215 $a1 online resource (xvi, 88 pages) ;$d26 cm 225 0 $aDirections in development 300 $aDescription based upon print version of record. 311 $a1-4648-0101-0 311 $a1-306-41156-4 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Contents; Foreword; Acknowledgments; About the Authors; Abbreviations; Chapter 1 The Nature, Scale, and Scope of Private Sector Responses to Crime and Violence; Introduction; Study Scope and Methods; Box 1.1 Literature Review on the Role of Firms in Environments Affected by Violence and Conflict; Boxes; Note; References; Chapter 2 Crime, Violence, and the Economy; Factors Contributing to Crime and Violence; Figure 2.1 Countries with the Highest Homicide Rates; Figure 2.2 Homicide Rates in Case Study Countries; Indicators of Crime and Violence; Figures 327 $aFigure 2.3 Homicide Rate Trends in Central America, Selected Countries, 1999-2009 Comparing the Impacts of Crime and Violence; Figure 2.4 Security Constraints and Costs of Doing Business in Case Study Countries Relative to Global Averages; References; Chapter 3 Coping Mechanisms of Private Firms: Analysis of Global Cases; Overview of Case Studies; How Crime and Violence Affect Firms; Table 3.1 Overview of Case Studies for How Firms Cope with Crime and Violence; Tables; Coping Mechanisms; Table 3.2 Matrix of Firm Strategies to Cope with Crime and Violence; Analysis and Lessons Learned 327 $aPolicy Implications Notes; References; Chapter 4 World Bank Group Work: From Policies and Research to Operational Initiatives; Growing Focus on Crime and Violence; Private Sector Development (PSD) Initiatives; Table 4.1 Recent World Bank CASs and CPSs Addressing Crime and Violence in Latin America and the Caribbean; Non-PSD Initiatives; Box 4.1 Public-Private Dialogue in Investment Climate Interventions; Notes; References; Chapter 5 World Bank Group Support for Private Sector Development in Environments of Crime and Violence; Opportunities for Support; Moving the Agenda Forward 327 $aOperational and Research Issues Notes; References; Case 1: Medelli?n, Colombia-How the Public and Private Sectors Have Coped with Violence; Chapter 6 Case Studies; Table 6.1 Medelli?n, Colombia: Summary of Key Crime and Violence Indicators and Coping Mechanisms; Figure 6.1 Homicide Rates in Medelli?n, Colombia, 1965-2008; Case 2: Rio de Janeiro, Brazil-The Favelas and the Private Sector: An Increasingly Safe Bet?; Table 6.2 Rio de Janeiro: Summary of Key Crime and Violence Indicators and Coping Mechanisms; Case 3: Jamaica-Coping with Violence in Paradise 327 $aTable 6.3 Jamaica: Summary of Key Crime and Violence Indicators and Coping Mechanisms Figure 6.2 Impact of Crime on Selected Business Practices in Jamaica, 2001; Table 6.4 Victimization of Firms, by Sector and Type of Crime in Jamaica, 2001; Figure 6.3 Private Security Costs as Percentage of Firm Revenue, by Firm Size, in Jamaica, 2001; Figure 6.4 Crime Protection Actions by Firms in Jamaica; Figure 6.5 Flankers Peace & Justice Center, Jamaica, Built with Support from Sandals Foundation; Case 4: Mexico-Public-Private Responses to Violence 327 $aTable 6.5 Mexico: Summary of Key Crime and Violence Indicators and Coping Mechanisms 330 $aCrime and violence inflict high costs on the private sector-costs that are rising globally, according to the World Bank's Enterprise Surveys, discussions with chambers and associations, and the Bank's Country Partnership Strategies, which reference the losses in terms of gross domestic product (GDP). In Latin America and the Caribbean, for example, losses due to crime and violence have been estimated at 9 percent of GDP in Honduras, 7.7 percent in El Salvador, and 3.6 percent in Costa Rica. In sectors such as clothing assembly, international purchasers can shift know-how and capital quickly to 410 0$aWorld Bank e-Library. 606 $aIndustries 606 $aIndustrial location$xSocial aspects 606 $aIndustries$xSecurity measures 606 $aCrime$xEconomic aspects 606 $aViolence$xEconomic aspects 615 0$aIndustries. 615 0$aIndustrial location$xSocial aspects. 615 0$aIndustries$xSecurity measures. 615 0$aCrime$xEconomic aspects. 615 0$aViolence$xEconomic aspects. 676 $a364.2/5 700 $aGoldberg$b Mike$f1956-$0276438 801 0$bDLC 801 1$bDLC 801 2$bDLC 906 $aBOOK 912 $a9910791321903321 996 $aHow firms cope with crime and violence$93763458 997 $aUNINA LEADER 02218oam 22004814a 450 001 9910328158503321 005 20230621141349.0 010 $a607-564-071-1 010 $a968-12-0895-1 035 $a(CKB)4100000008491423 035 $a(OCoLC)1108162021 035 $a(MdBmJHUP)muse85155 035 $a(WaSeSS)IndRDA00124471 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/89361 035 $a(oapen)doab89361 035 $a(EXLCZ)994100000008491423 100 $a19990816d1999 uy 0 101 0 $aspa 135 $aur|||||||nn|n 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aFamilia y educación en Iberoamérica$fPilar Gonzalbo Aizpuru, coordinadora 205 $a1a ed. 210 $cEl Colegio de México$d2003 210 1$aMexico, D.F. :$cCentro de Estudios Histo?ricos, Colegio de Mexico,$d1999. 210 4$d©1999. 215 $a1 online resource (385 p.) $cill. ; 320 $aIncludes bibliographical references. 330 $aEl objeto de estudio que los autores de este libro desarrollan en cuatro apartados se centra en el análisis de lo que se entiende por educación y cómo se relacionan los procesos educativos familiares e institucionales, cómo se encadenan educación y costumbres, cómo difieren o se desarrollan estos ámbitos según época, clase, religión, élites, Estado, padres, tradición, modernidad, prejuicios, cultura. Los ensayos versan sobre la educación al servicio de un proyecto integral, la moral como educación y los conflictos de modernidad, la mujer como protagonista de la educación familiar, y el mundo indígena: valores, prejuicios y criterios de modernidad. 606 $aEducation$xSocial aspects$zLatin America$xHistory 606 $aHome and school$zLatin America$xHistory 615 0$aEducation$xSocial aspects$xHistory. 615 0$aHome and school$xHistory. 676 $a370.98 700 $aGonzalbo$b Pilar$4auth 701 $aGonzalbo$b Pilar$f1935-$01022378 801 0$bMdBmJHUP 801 1$bMdBmJHUP 906 $aBOOK 912 $a9910328158503321 996 $aFamilia y educación en Iberoamérica$92435890 997 $aUNINA