LEADER 05590nam 22006974a 450 001 9910824456303321 005 20200520144314.0 010 $a1-280-96289-5 010 $a9786610962891 010 $a0-08-047142-0 035 $a(CKB)1000000000350068 035 $a(EBL)287974 035 $a(OCoLC)213298555 035 $a(SSID)ssj0000156848 035 $a(PQKBManifestationID)11182691 035 $a(PQKBTitleCode)TC0000156848 035 $a(PQKBWorkID)10131386 035 $a(PQKB)11529276 035 $a(Au-PeEL)EBL287974 035 $a(CaPaEBR)ebr10167046 035 $a(CaONFJC)MIL96289 035 $a(MiAaPQ)EBC287974 035 $a(EXLCZ)991000000000350068 100 $a20070915d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aForecasting volatility in the financial markets /$fedited by John Knight, Stephen Satchell 205 $a3rd ed. 210 $aAmsterdam ;$aBoston $cButterworth-Heinemann$d2007 215 $a1 online resource (428 p.) 225 1 $aQuantitative finance series 300 $aDescription based upon print version of record. 311 $a0-7506-6942-X 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Forecasting Volatility in the Financial Markets; Copyright Page; Table of Contents; List of contributors; Preface to Third Edition; Introduction; Chapter 1 Volatility modelling and forecasting in finance; 1.1 Introduction; 1.2 Autoregressive moving average models; 1.3 Changes in volatility; 1.3.1 Volatility in financial time series: stylized facts; 1.3.2 The basic set-up; 1.4 ARCH models; 1.4.1 Generalized ARCH; 1.4.2 Integrated ARCH; 1.4.3 Exponential ARCH; 1.4.4 ARCH-M model; 1.4.5 Fractionally integrated ARCH; 1.4.6 Other univariate ARCH formulations 327 $a1.4.7 Multivariate ARCH models1.5 Stochastic variance models; 1.5.1 From continuous time financial models to discrete time SV models; 1.5.2 Persistence and the SV model; 1.5.3 Long memory SV models; 1.5.4 Risk-return trade-off in SV models; 1.5.5 Multivariate SV models; 1.6 Structural changes in the underlying process; 1.6.1 Regime switching models; 1.6.2 Extensions of the regime switching models; 1.7 Threshold models; 1.7.1 Self-exciting threshold models; 1.7.2 Open loop threshold models; 1.7.3 Closed loop threshold models; 1.7.4 Smooth threshold autoregressive models 327 $a1.7.5 Identification in SETAR models1.7.6 A threshold AR(1) model; 1.7.7 A threshold MA model; 1.7.8 Threshold models and asymmetries in volatility; 1.7.9 Testing for non-linearity; 1.7.10 Threshold estimation and prediction of TAR models; 1.8 Volatility forecasting; 1.8.1 Volatility forecasting based on time-series models; 1.8.2 Volatility forecasting based on option ISD (Implied Standard Deviation); 1.9 Conclusion; References and further reading; Notes; Chapter 2 What good is a volatility model?; Abstract; 2.1 Introduction; 2.1.1 Notation; 2.1.2 Types of volatility models 327 $a2.2 Stylized facts about asset price volatility2.2.1 Volatility exhibits persistence; 2.2.2 Volatility is mean reverting; 2.2.3 Innovations may have an asymmetric impact on volatility; 2.2.4 Exogenous variables may influence volatility; 2.2.5 Tail probabilities; 2.2.6 Forecast evaluation; 2.3 An empirical example; 2.3.1 Summary of the data; 2.3.2 A volatility model; 2.3.3 Mean reversion and persistence in volatility; 2.3.4 An asymmetric volatility model; 2.3.5 A model with exogenous volatility regressors; 2.3.6 Aggregation of volatility models 327 $a2.4 Conclusions and challenges for future researchReferences; Notes; Chapter 3 Applications of portfolio variety; Abstract; 3.1 Introduction; 3.2 Some applications of variety; 3.3 Empirical research on variety; 3.4 Variety and risk estimation; 3.5 Variety as an explanation of active management styles; 3.6 Summary; References; Chapter 4 A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices; 4.1 Introduction; 4.2 Data; 4.3 Theory and empirical methodology; 4.3.1 Realized variance; 4.3.2 Optimal sampling frequency; 4.3.3 Estimation; 4.3.4 Forecasting 327 $a4.4 Initial data analysis 330 $aThis new edition of Forecasting Volatility in the Financial Markets assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding o 410 0$aQuantitative finance series. 606 $aOptions (Finance)$xMathematical models 606 $aSecurities$xPrices$xMathematical models 606 $aStock price forecasting$xMathematical models 615 0$aOptions (Finance)$xMathematical models. 615 0$aSecurities$xPrices$xMathematical models. 615 0$aStock price forecasting$xMathematical models. 676 $a332.66/2042 701 $aKnight$b John L$01610775 701 $aSatchell$b S$g(Stephen)$01156060 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910824456303321 996 $aForecasting volatility in the financial markets$94202677 997 $aUNINA