01046nam a2200301 i 450099100103332970753620020507182010.0930515s1990 uk ||| | eng 0521386209b10791802-39ule_instLE01306025ExLDip.to Matematicaeng514.3202AMS 54EAMS 54E15James, Ioan Mackenzie117816Introduction to uniform spaces /I. M. JamesCambridge :Cambridge University Press,1990148 p. ;23 cmLondon Mathematical Society lecture note series,0076-0552 ;144Uniform spacesUniform structures.b1079180223-02-1728-06-02991001033329707536LE013 54E JAM11 (1990)12013000290157le013-E0.00-l- 03030.i1089242428-06-02Introduction to uniform spaces921343UNISALENTOle01301-01-93ma -enguk 0101157nam0 22002771i 450 UON0014875120231205102912.74308-04-72537-320020107d1995 |0itac50 baengUS||||p |||||Literature of the lost homeKobayashi HideoCriticism literary 1924-1939edited and translated and with and introduction by Paul Anderer177 p.22 cm¦LETTERATURA GIAPPONESECRITICA LETTERARIASEC. XXUONC032026FIUSStanford (CA)UONL000066GIA VI BGIAPPONE - LETTERATURA MODERNA E CONTEMPORANEAAKOBAYASHI HideoUONV035827635613ANDERERPaulUONV089062Stanford University PressUONV246208650ITSOL20250307RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00148751SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI GIA VI B 296 N SI SA 100429 7 296 N Literature of the lost home1276517UNIOR05420nam 2200757Ia 450 991081442200332120200520144314.09786612547744978128254774212825477479780470688014047068801797804706880210470688025(CKB)2670000000014746(EBL)514415(OCoLC)609862847(SSID)ssj0000356704(PQKBManifestationID)11275000(PQKBTitleCode)TC0000356704(PQKBWorkID)10350294(PQKB)11490533(MiAaPQ)EBC514415(Au-PeEL)EBL514415(CaPaEBR)ebr10377794(CaONFJC)MIL254774(OCoLC)1292943647(FINmELB)ELB179012(Perlego)2751497(EXLCZ)99267000000001474620091217d2010 uy 0engur|n|---|||||txtccrARCH models for financial applications /Evdokia Xekalaki, Stavros Degiannakis1st ed.Chichester ;Hoboken John Wiley & Sons20101 online resource (560 p.)Description based upon print version of record.9780470066300 047006630X Includes bibliographical references and index.ARCH Models for Financial Applications; Contents; Preface; Notation; 1 What is an ARCH process?; 1.1 Introduction; 1.2 The autoregressive conditionally heteroscedastic process; 1.3 The leverage effect; 1.4 The non-trading period effect; 1.5 The non-synchronous trading effect; 1.6 The relationship between conditional variance and conditional mean; 1.6.1 The ARCH in mean model; 1.6.2 Volatility and serial correlation; 2 ARCH volatility specifications; 2.1 Model specifications; 2.2 Methods of estimation; 2.2.1 Maximum likelihood estimation; 2.2.2 Numerical estimation algorithms2.2.3 Quasi-maximum likelihood estimation2.2.4 Other estimation methods; 2.3 Estimating the GARCH model with EViews 6: an empirical example; 2.4 Asymmetric conditional volatility specifications; 2.5 Simulating ARCH models using EViews; 2.6 Estimating asymmetric ARCH models with G@RCH 4.2 OxMetrics: an empirical example; 2.7 Misspecification tests; 2.7.1 The Box-Pierce and Ljung-Box Q statistics; 2.7.2 Tse's residual based diagnostic test for conditional heteroscedasticity; 2.7.3 Engle's Lagrange multiplier test; 2.7.4 Engle and Ng's sign bias tests2.7.5 The Breusch-Pagan, Godfrey, Glejser, Harvey and White tests2.7.6 The Wald, likelihood ratio and Lagrange multiplier tests; 2.8 Other ARCH volatility specifications; 2.8.1 Regime-switching ARCH models; 2.8.2 Extended ARCH models; 2.9 Other methods of volatility modelling; 2.10 Interpretation of the ARCH process; Appendix; 3 Fractionally integrated ARCH models; 3.1 Fractionally integrated ARCH model specifications; 3.2 Estimating fractionally integrated ARCH models using G@RCH 4.2 OxMetrics: an empirical example3.3 A more detailed investigation of the normality of the standardized residuals: goodness-of-fit tests3.3.1 EDF tests; 3.3.2 Chi-square tests; 3.3.3 QQ plots; 3.3.4 Goodness-of-fit tests using EViews and G@RCH; Appendix; 4 Volatility forecasting: an empirical example using EViews 6; 4.1 One-step-ahead volatility forecasting; 4.2 Ten-step-ahead volatility forecasting; Appendix; 5 Other distributional assumptions; 5.1 Non-normally distributed standardized innovations5.2 Estimating ARCH models with non-normally distributed standardized innovations using G@RCH 4.2 OxMetrics: an empirical example5.3 Estimating ARCH models with non-normally distributed standardized innovations using EViews 6: an empirical example; 5.4 Estimating ARCH models with non-normally distributed standardized innovations using EViews 6: the logl object; Appendix; 6 Volatility forecasting: an empirical example using G@RCH Ox; Appendix; 7 Intraday realized volatility models; 7.1 Realized volatility; 7.2 Intraday volatility models7.3 Intraday realized volatility andARFIMAXmodels in G@RCH 4.2 OxMetrics: an empirical exampleAutoregressive Conditional Heteroskedastic (ARCH) processes are used in finance to model asset price volatility over time. This book introduces both the theory and applications of ARCH models and provides the basic theoretical and empirical background, before proceeding to more advanced issues and applications. The Authors provide coverage of the recent developments in ARCH modelling which can be implemented using econometric software, model construction, fitting and forecasting and model evaluation and selection. Key Features:Presents a comprehensive overview of both tFinanceMathematical modelsAutoregression (Statistics)FinanceMathematical models.Autoregression (Statistics)332.015195332.01519536Xekalaki Evdokia614604Degiannakis Stavros614605MiAaPQMiAaPQMiAaPQBOOK9910814422003321ARCH models for financial applications1131618UNINA