LEADER 01754nam 2200409Ia 450 001 996386259203316 005 20221108032351.0 035 $a(CKB)1000000000620564 035 $a(EEBO)2240935300 035 $a(OCoLC)9920393000971 035 $a(EXLCZ)991000000000620564 100 $a19910611d1572 uy | 101 0 $aeng 135 $aurbn||||a|bb| 200 03$a[A Paraphrase vppon the epistle of the holie apostle S. Paule to the Romanes ...]$b[electronic resource] 210 $aImprinted at London $cHenry Bynneman for William Norton$d[1572?] 215 $a[18+], 96 [i.e 191] p 300 $aT.p. lacking; title taken from inserted t.p. from New College, London, Eng. Library copy. 300 $aDedication signed: T. Paulfreyman. 300 $aImprint from colophon; date of imprint suggested by STC (2nd ed.). 300 $aPages numbered on recto only. 300 $aErrors in paging: p. 58 and 60 misnumbered 62 and 64 respectively. 300 $aIncludes letter written by Ulrich Zwingli, several tracts by Martinus Cellarius [i.e. Martin Borrhaus], and exhortation written by Edward Seymour (reprint of STC 22268). 300 $aImperfect: torn, with loss of print. 300 $aReproduction of original in the British Library. 330 $aeebo-0018 701 $aPalfreyman$b Thomas$fd. 1589?$01002375 701 $aZwingli$b Ulrich$f1484-1531.$0204525 701 $aBorrhaus$b Martin$f1499-1564.$0908751 701 $aSomerset$b Edward Seymour$cDuke of,$f1506?-1552.$01002376 801 0$bEBK 801 1$bEBK 801 2$bWaOLN 906 $aBOOK 912 $a996386259203316 996 $aA Paraphrase vppon the epistle of the holie apostle S. Paule to the Romanes ...$92300659 997 $aUNISA LEADER 05830nam 2200805Ia 450 001 9910811779903321 005 20200520144314.0 010 $a9786613332844 010 $a9781283332842 010 $a1283332841 010 $a9781118204580 010 $a1118204581 010 $a9781118204566 010 $a1118204565 010 $a9781118204634 010 $a1118204638 035 $a(CKB)2550000000064746 035 $a(EBL)818537 035 $a(OCoLC)768572208 035 $a(SSID)ssj0000554839 035 $a(PQKBManifestationID)11344552 035 $a(PQKBTitleCode)TC0000554839 035 $a(PQKBWorkID)10517290 035 $a(PQKB)11036417 035 $a(MiAaPQ)EBC818537 035 $a(Au-PeEL)EBL818537 035 $a(CaPaEBR)ebr10510644 035 $a(CaONFJC)MIL333284 035 $a(iGPub)WILEYB0016091 035 $a(Perlego)1013263 035 $a(EXLCZ)992550000000064746 100 $a20110921d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aHandbook of modeling high-frequency data in finance /$fFrederi G. Viens, Maria C. Mariani, Ionut Florescu 205 $a1. 210 $aHoboken, NJ $cWiley$dc2012 215 $a1 online resource (457 p.) 225 1 $aWiley handbooks in financial engineering and econometrics ;$v4 300 $aDescription based upon print version of record. 311 08$a9780470876886 311 08$a0470876883 320 $aIncludes bibliographical references and index. 327 $aHandbook of Modeling High-Frequency Data in Finance; Contents; Preface; Contributors; Part One Analysis of Empirical Data; 1 Estimation of NIG and VG Models for High Frequency Financial Data; 1.1 Introduction; 1.2 The Statistical Models; 1.3 Parametric Estimation Methods; 1.4 Finite-Sample Performance via Simulations; 1.5 Empirical Results; 1.6 Conclusion; References; 2 A Study of Persistence of Price Movement using High Frequency Financial Data; 2.1 Introduction; 2.2 Methodology; 2.3 Results; 2.4 Rare Events Distribution; 2.5 Conclusions; References 327 $a3 Using Boosting for Financial Analysis and Trading3.1 Introduction; 3.2 Methods; 3.3 Performance Evaluation; 3.4 Earnings Prediction and Algorithmic Trading; 3.5 Final Comments and Conclusions; References; 4 Impact of Correlation Fluctuations on Securitized structures; 4.1 Introduction; 4.2 Description of the Products and Models; 4.3 Impact of Dynamics of Default Correlation on Low-Frequency Tranches; 4.4 Impact of Dynamics of Default Correlation on High-Frequency Tranches; 4.5 Conclusion; References; 5 Construction of Volatility Indices Using A Multinomial Tree Approximation Method 327 $a5.1 Introduction5.2 New Methodology; 5.3 Results and Discussions; 5.4 Summary and Conclusion; References; Part Two Long Range Dependence Models; 6 Long Correlations Applied to the Study of Memory Effects in High Frequency (TICK) Data, the Dow Jones Index, and International Indices; 6.1 Introduction; 6.2 Methods Used for Data Analysis; 6.3 Data; 6.4 Results and Discussions; 6.5 Conclusion; References; 7 Risk Forecasting with GARCH, Skewed t Distributions, and Multiple Timescales; 7.1 Introduction; 7.2 The Skewed t Distributions; 7.3 Risk Forecasts on a Fixed Timescale 327 $a7.4 Multiple Timescale Forecasts7.5 Backtesting; 7.6 Further Analysis: Long-Term GARCH and Comparisons using Simulated Data; 7.7 Conclusion; References; 8 Parameter Estimation and Calibration for Long-Memory Stochastic Volatility Models; 8.1 Introduction; 8.2 Statistical Inference Under the LMSV Model; 8.3 Simulation Results; 8.4 Application to the S&P Index; 8.5 Conclusion; References; Part Three Analytical Results; 9 A Market Microstructure Model of Ultra High Frequency Trading; 9.1 Introduction; 9.2 Microstructural Model; 9.3 Static Comparisons; 9.4 Questions for Future Research 327 $aReferences10 Multivariate Volatility Estimation with High Frequency Data Using Fourier Method; 10.1 Introduction; 10.2 Fourier Estimator of Multivariate Spot Volatility; 10.3 Fourier Estimator of Integrated Volatility in the Presence of Microstructure Noise; 10.4 Fourier Estimator of Integrated Covariance in the Presence of Microstructure Noise; 10.5 Forecasting Properties of Fourier Estimator; 10.6 Application: Asset Allocation; References; 11 The "Retirement" Problem; 11.1 Introduction; 11.2 The Market Model; 11.3 Portfolio and Wealth Processes; 11.4 Utility Function 327 $a11.5 The Optimization Problem in the Case p(t,T] o 0 330 $aCUTTING-EDGE DEVELOPMENTS IN HIGH-FREQUENCY FINANCIAL ECONOMETRICS In recent years, the availability of high-frequency data and advances in computing have allowed financial practitioners to design systems that can handle and analyze this information. Handbook of Modeling High-Frequency Data in Finance addresses the many theoretical and practical questions raised by the nature and intrinsic properties of this data. A one-stop compilation of empirical and analytical research, this handbook explores data sampled with high-frequency finance in financial engineering, stati 410 0$aWiley handbooks in financial engineering and econometrics ;$v4. 606 $aFinance$xEconometric models 606 $aEconometric models 615 0$aFinance$xEconometric models. 615 0$aEconometric models. 676 $a332.01/5195 686 $aBUS027000$2bisacsh 700 $aViens$b Frederi G.$f1969-$01609150 701 $aFlorescu$b Ionut$f1973-$0525052 701 $aMariani$b Maria C$0862418 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910811779903321 996 $aHandbook of modeling high-frequency data in finance$93936264 997 $aUNINA LEADER 01755nam 22004693 450 001 9911027076103321 005 20250914090806.0 010 $a1-394-41132-4 010 $a1-394-41125-1 035 $a(CKB)40924068000041 035 $a(MiAaPQ)EBC32293644 035 $a(Au-PeEL)EBL32293644 035 $a(OCoLC)1541781183 035 $a(EXLCZ)9940924068000041 100 $a20250914d2025 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDriving Innovation Through AI and Digital Twin for 6G Powered Sustainable Ultra Smart Cities 205 $a1st ed. 210 1$aNewark :$cJohn Wiley & Sons, Incorporated,$d2025. 210 4$dİ2025. 215 $a1 online resource (324 pages) 225 1 $aISTE Invoiced Series 311 08$a1-83669-040-1 330 $aThis book presents the 6G powered integration of Artificial Intelligence (AI) and Digital Twin (DT) technology for sustainable smart cities.In the context of smart cities, 6G, AI and DT hold enormous potential for transformation by boosting city infrastructure and planning, streamlining healthcare facilities, and improving transportation. 410 0$aISTE Invoiced Series 676 $a307.76028563 700 $aTaneja$b Ashu$01848706 701 $aKumar$b Abhishek$0977677 701 $aVishnudas Limkar$b Suresh$01848707 701 $aOuaissa$b Mariya$01380452 701 $aOuaissa$b Mariyam$01848708 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911027076103321 996 $aDriving Innovation Through AI and Digital Twin for 6G Powered Sustainable Ultra Smart Cities$94435998 997 $aUNINA