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Biblioteca

MARC Lista (tabellare)
Handbook of modeling high-frequency data in finance [[electronic resource] /] / Frederi G. Viens, Maria C. Mariani, Ionut Florescu
Handbook of modeling high-frequency data in finance [[electronic resource] /] / Frederi G. Viens, Maria C. Mariani, Ionut Florescu
Autore Viens Frederi G. <1969->
Edizione [1.]
Pubbl/distr/stampa Hoboken, NJ, : Wiley, c2012
Descrizione fisica 1 online resource (457 p.)
Disciplina 332.01/5195
Altri autori (Persone) FlorescuIonuţ <1973->
MarianiMaria C
Collana Wiley handbooks in financial engineering and econometrics
Soggetto topico Finance - Econometric models
Econometric models
ISBN 1-283-33284-1
9786613332844
1-118-20458-1
1-118-20456-5
1-118-20463-8
Classificazione BUS027000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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; 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
Record Nr. UNINA-9910139556403321
Viens Frederi G. <1969->  
Hoboken, NJ, : Wiley, c2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Handbook of modeling high-frequency data in finance / / Frederi G. Viens, Maria C. Mariani, Ionut Florescu
Handbook of modeling high-frequency data in finance / / Frederi G. Viens, Maria C. Mariani, Ionut Florescu
Autore Viens Frederi G. <1969->
Edizione [1.]
Pubbl/distr/stampa Hoboken, NJ, : Wiley, c2012
Descrizione fisica 1 online resource (457 p.)
Disciplina 332.01/5195
Altri autori (Persone) FlorescuIonut <1973->
MarianiMaria C
Collana Wiley handbooks in financial engineering and econometrics
Soggetto topico Finance - Econometric models
Econometric models
ISBN 9786613332844
9781283332842
1283332841
9781118204580
1118204581
9781118204566
1118204565
9781118204634
1118204638
Classificazione BUS027000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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; 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
Record Nr. UNINA-9910811779903321
Viens Frederi G. <1969->  
Hoboken, NJ, : Wiley, c2012
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui