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1. |
Record Nr. |
UNISA996386259203316 |
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Titolo |
[A Paraphrase vppon the epistle of the holie apostle S. Paule to the Romanes ...] [[electronic resource]] |
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Pubbl/distr/stampa |
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Imprinted at London, : Henry Bynneman for William Norton, [1572?] |
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Descrizione fisica |
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Altri autori (Persone) |
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PalfreymanThomas <d. 1589?> |
ZwingliUlrich <1484-1531.> |
BorrhausMartin <1499-1564.> |
SomersetEdward Seymour, Duke of, <1506?-1552.> |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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T.p. lacking; title taken from inserted t.p. from New College, London, Eng. Library copy. |
Dedication signed: T. Paulfreyman. |
Imprint from colophon; date of imprint suggested by STC (2nd ed.). |
Pages numbered on recto only. |
Errors in paging: p. 58 and 60 misnumbered 62 and 64 respectively. |
Includes letter written by Ulrich Zwingli, several tracts by Martinus Cellarius [i.e. Martin Borrhaus], and exhortation written by Edward Seymour (reprint of STC 22268). |
Imperfect: torn, with loss of print. |
Reproduction of original in the British Library. |
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Sommario/riassunto |
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2. |
Record Nr. |
UNINA9910811779903321 |
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Autore |
Viens Frederi G. <1969-> |
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Titolo |
Handbook of modeling high-frequency data in finance / / Frederi G. Viens, Maria C. Mariani, Ionut Florescu |
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Pubbl/distr/stampa |
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Hoboken, NJ, : Wiley, c2012 |
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ISBN |
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9786613332844 |
9781283332842 |
1283332841 |
9781118204580 |
1118204581 |
9781118204566 |
1118204565 |
9781118204634 |
1118204638 |
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Edizione |
[1.] |
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Descrizione fisica |
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1 online resource (457 p.) |
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Collana |
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Wiley handbooks in financial engineering and econometrics ; ; 4 |
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Classificazione |
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Altri autori (Persone) |
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FlorescuIonut <1973-> |
MarianiMaria C |
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Disciplina |
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Soggetti |
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Finance - Econometric models |
Econometric models |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Handbook 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 |
3 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; |
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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 |
5.1 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 |
7.4 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 |
References10 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 |
11.5 The Optimization Problem in the Case p(t,T] o 0 |
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Sommario/riassunto |
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CUTTING-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 |
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