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Econometrics of financial high-frequency data / Nikolaus Hautsch.

By: Material type: TextTextLanguage: English Publication details: Berlin : Springer-Verlag, 2012.Description: xiii, 371 páginas : tablas, gráficas ; 24 cmContent type:
  • Texto
Media type:
  • Sin mediación
Carrier type:
  • Volumen
ISBN:
  • 9783642219245
Subject(s): DDC classification:
  • 332.6 H18e 21
Other classification:
  • F30
Contents:
1. Introduction: 1.1.Motivation ; 1.2. Structure of the book -- 2. Microstructure foundations: 2.1. The institutional framework of trading ; 2.2. A Review of market microstructure theory -- 3. Empirical properties of high-frequency data: 3.1. Handling high-frequency data ; 3.2. Aggregation by trading events: financial durations ; 3.3. Properties of financial durations ; 3.4. Properties of trading characteristics ; 3.5. Properties of time aggregated data ; 3.6. Summary of major empirical findings -- 4. Financial point processes: 4.1. Basic concepts of point processes ; 4.2. Four ways to model point processes ; 4.3. Censoring and time-varying covariates ; 4.4. An outlook on dynamic extensions -- 5.Univariate multiplicative error models: 5.1. ARMA models for log variables ; 5.2. A MEM for durations: the ACD model ; 5.3. Estimation of the ACD model ; 5.4. Seasonality’s and explanatory variables ; 5.5. The Log-ACD model ; 5.6. Testing the ACD model -- 6.Generalized multiplicative error models: 6.1. A Class of augmented ACD models ; 6.2. Regime-switching ACD models ; 6.3. Long memory ACD models ; 6.4. Mixture and component multiplicative error ; 6.5. Further generalizations of multiplicative error models -- 7.Vector multiplicative error models: 7.1. VMEM Processes ; 7.2. Stochastic vector multiplicative error models -- 8. Modelling high-frequency volatility: 8.1. Intraday quadratic variation measures ; 8.2. Spot variances and jumps ; 8.3.Trade-based volatility measures ; 8.4. Volatility measurement using price durations ; 8.5. Modelling quote volatility -- 9.Estimating market liquidity: 9.1.Simple spread and price impact measures ; 9.2. Volume based measures ; 9.3. Modelling order book depth -- 10. Semiparametric dynamic proportional hazard models: 10.1. Dynamic integrated hazard processes ; 10.2. The semiparametric ACPH model ; 10.3. Properties of the semiparametric ACPH model ; 10.4. Extended SACPH models ; 10.5. Testing the SACPH model ; 10.6. Estimating Volatility Using the SACPH model -- 11.Univariate Dynamic Intensity Models: 11.1. The autoregressive conditional Intensity Model ; 11.2. Generalized ACI models ; 11.3. Hawkes processes -- 12. Multivariate dynamic intensity models: 12.1. Multivariate ACI models ; 12.2. Applications of multivariate ACI models ; 12.3. Multivariate Hawkes processes ; 12.4. Stochastic conditional intensity processes ; 12.5. SCI Modelling of multivariate price intensities -- 13. Autoregressive discrete processes and quote dynamics: 13.1. Univariate dynamic count data models ; 13.2. Multivariate ACP models ; 13.3. A Simple model for transaction price dynamics ; 13.4. Autoregressive conditional multinomial models ; 13.5. Autoregressive models for integer-valued variables ; 13.6. Modelling ask and bid quote dynamics.
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Holdings
Item type Home library Call number Vol info Status Notes Date due Barcode Item holds
LIBRO FISICO Biblioteca Principal 332.6 H18e (Browse shelf(Opens below)) Ejemplar 1 Available Mantener en colección. 29004025502559
Total holds: 0

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1. Introduction: 1.1.Motivation ; 1.2. Structure of the book -- 2. Microstructure foundations: 2.1. The institutional framework of trading ; 2.2. A Review of market microstructure theory -- 3. Empirical properties of high-frequency data: 3.1. Handling high-frequency data ; 3.2. Aggregation by trading events: financial durations ; 3.3. Properties of financial durations ; 3.4. Properties of trading characteristics ; 3.5. Properties of time aggregated data ; 3.6. Summary of major empirical findings -- 4. Financial point processes: 4.1. Basic concepts of point processes ; 4.2. Four ways to model point processes ; 4.3. Censoring and time-varying covariates ; 4.4. An outlook on dynamic extensions -- 5.Univariate multiplicative error models: 5.1. ARMA models for log variables ; 5.2. A MEM for durations: the ACD model ; 5.3. Estimation of the ACD model ; 5.4. Seasonality’s and explanatory variables ; 5.5. The Log-ACD model ; 5.6. Testing the ACD model -- 6.Generalized multiplicative error models: 6.1. A Class of augmented ACD models ; 6.2. Regime-switching ACD models ; 6.3. Long memory ACD models ; 6.4. Mixture and component multiplicative error ; 6.5. Further generalizations of multiplicative error models -- 7.Vector multiplicative error models: 7.1. VMEM Processes ; 7.2. Stochastic vector multiplicative error models -- 8. Modelling high-frequency volatility: 8.1. Intraday quadratic variation measures ; 8.2. Spot variances and jumps ; 8.3.Trade-based volatility measures ; 8.4. Volatility measurement using price durations ; 8.5. Modelling quote volatility -- 9.Estimating market liquidity: 9.1.Simple spread and price impact measures ; 9.2. Volume based measures ; 9.3. Modelling order book depth -- 10. Semiparametric dynamic proportional hazard models: 10.1. Dynamic integrated hazard processes ; 10.2. The semiparametric ACPH model ; 10.3. Properties of the semiparametric ACPH model ; 10.4. Extended SACPH models ; 10.5. Testing the SACPH model ; 10.6. Estimating Volatility Using the SACPH model -- 11.Univariate Dynamic Intensity Models: 11.1. The autoregressive conditional Intensity Model ; 11.2. Generalized ACI models ; 11.3. Hawkes processes -- 12. Multivariate dynamic intensity models: 12.1. Multivariate ACI models ; 12.2. Applications of multivariate ACI models ; 12.3. Multivariate Hawkes processes ; 12.4. Stochastic conditional intensity processes ; 12.5. SCI Modelling of multivariate price intensities -- 13. Autoregressive discrete processes and quote dynamics: 13.1. Univariate dynamic count data models ; 13.2. Multivariate ACP models ; 13.3. A Simple model for transaction price dynamics ; 13.4. Autoregressive conditional multinomial models ; 13.5. Autoregressive models for integer-valued variables ; 13.6. Modelling ask and bid quote dynamics.

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