Notice bibliographique
- Notice
Type(s) de contenu et mode(s) de consultation : Texte noté : électronique
Auteur(s) : Hautsch, Nikolaus
Titre(s) : Econometrics of financial high-frequency data [Texte électronique] / Nikolaus Hautsch
Publication : Berlin ; New York : Springer, cop. 2012
Description matérielle : 1 ressource dématérialisée
Note(s) : Includes bibliographical references and index
Sujet(s) : Économétrie
Finances -- Modèles économétriques
Taux de change -- Modèles économétriques
Börsenhandel
Volatilität
Ökonometrisches Modell
Identifiants, prix et caractéristiques : ISBN 9783642219252
Identifiant de la notice : ark:/12148/cb44702424t
Notice n° :
FRBNF44702424
(notice reprise d'un réservoir extérieur)
Table des matières : Machine generated contents note: 1. Introduction ; 1.1. Motivation ; 1.2. Structure
of the Book ; References ; 2. Microstructure Foundations ; 2.1. The Institutional
Framework of Trading ; 2.1.1. Types of Traders and Forms of Trading ; 2.1.2. Types
of Orders ; 2.1.3. Market Structures ; 2.1.4. Order Precedence and Pricing Rules
; 2.1.5. Trading Forms at Selected International Exchanges ; 2.2.A Review of Market
Microstructure Theory ; 2.2.1. Asymmetric Information Based Models ; 2.2.2. Inventory
Models ; 2.2.3. Major Implications for Trading Variables ; 2.2.4. Models for Limit
Order Book Markets ; References ; 3. Empirical Properties of High-Frequency Data
; 3.1. Handling High-Frequency Data ; 3.1.1. Databases and Trading Variables ;
3.1.2. Matching Trades and Quotes ; 3.1.3. Data Cleaning ; 3.1.4. Split-Transactions
; 3.1.5. Identification of Buyer- and Seller-Initiated Trades ; 3.2. Aggregation
by Trading Events: Financial Durations.
Note continued: 3.2.1. Trade and Order Arrival Durations ; 3.2.2. Price and Volume
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 ; References ; 4. Financial Point Processes ; 4.1. Basic Concepts
of Point Processes ; 4.1.1. Fundamental Definitions ; 4.1.2.Compensators and Intensities
; 4.1.3. The Homogeneous Poisson Process ; 4.1.4. Generalizations of Poisson Processes
; 4.1.5.A Random Time Change Argument ; 4.1.6. Intensity-Based Inference ; 4.1.7.
Simulation and Diagnostics ; 4.2. Four Ways to Model Point Processes ; 4.2.1. Intensity
Models ; 4.2.2. Hazard Models ; 4.2.3. Duration Models ; 4.2.4. Count Data Models
; 4.3. Censoring and Time-Varying Covariates ; 4.3.1. Censoring ; 4.3.2. Time-Varying
Covariates ; 4.4. An Outlook on Dynamic Extensions ; References ; 5. Univariate
Multiplicative Error Models.
Note continued: 5.1. ARMA Models for Log Variables ; 5.2.A MEM for Durations: The
ACD Model ; 5.3. Estimation of the ACD Model ; 5.3.1. QML Estimation ; 5.3.2. ML
Estimation ; 5.4. Seasonalities and Explanatory Variables ; 5.5. The Log-ACD Model
; 5.6. Testing the ACD Model ; 5.6.1. Portmanteau Tests ; 5.6.2. Independence Tests
; 5.6.3. Distribution Tests ; 5.6.4. Lagrange Multiplier Tests ; 5.6.5. Conditional
Moment Tests ; 5.6.6. Monte Carlo Evidence ; References ; 6. Generalized Multiplicative
Error Models ; 6.1.A Class of Augmented ACD Models ; 6.1.1. Special Cases ; 6.1.2.
Theoretical Properties ; 6.1.3. Empirical Illustrations ; 6.2. Regime-Switching
ACD Models ; 6.2.1. Threshold ACD Models ; 6.2.2. Smooth Transition ACD Models ;
6.2.3. Markov Switching ACD Models ; 6.3. Long Memory ACD Models ; 6.4. Mixture
and Component Multiplicative Error Models ; 6.4.1. The Stochastic Conditional Duration
Model ; 6.4.2. Stochastic Multiplicative Error Models.
Note continued: 6.4.3.Component Multiplicative Error Models ; 6.5. Further Generalizations
of Multiplicative Error Models ; 6.5.1.Competing Risks ACD Models ; 6.5.2. Semiparametric
ACD Models ; 6.5.3. Stochastic Volatility Duration Models ; References ; 7. Vector
Multiplicative Error Models ; 7.1. VMEM Processes ; 7.1.1. The Basic VMEM Specification
; 7.1.2. Statistical Inference ; 7.1.3. Applications ; 7.2. Stochastic Vector Multiplicative
Error Models ; 7.2.1. Stochastic VMEM Processes ; 7.2.2. Simulation-Based Inference
; 7.2.3. Modelling Trading Processes ; References ; 8. Modelling High-Frequency
Volatility ; 8.1. Intraday Quadratic Variation Measures ; 8.1.1. Maximum Likelihood
Estimation ; 8.1.2. The Realized Kernel Estimator ; 8.1.3. The Pre-averaging Estimator
; 8.1.4. Empirical Evidence ; 8.1.5. Modelling and Forecasting Intraday Variances
; 8.2. Spot Variances and Jumps ; 8.3. Trade-Based Volatility Measures.
Note continued: 8.4. Volatility Measurement Using Price Durations ; 8.5. Modelling
Quote Volatility ; References ; 9. Estimating Market Liquidity ; 9.1. Simple Spread
and Price Impact Measures ; 9.1.1. Spread Measures ; 9.1.2. Price Impact Measures
; 9.2. Volume Based Measures ; 9.2.1. The VNET Measure ; 9.2.2. Excess Volume Measures
; 9.3. Modelling Order Book Depth ; 9.3.1.A Cointegrated VAR Model for Quotes and
Depth ; 9.3.2.A Dynamic Nelson ; Siegel Type Order Book Model ; 9.3.3.A Semiparametric
Dynamic Factor Model ; References ; 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 ; 10.3.1. Autocorrelation
Structure ; 10.3.2. Estimation Quality ; 10.4. Extended SACPH Models ; 10.4.1.
Regime-Switching Baseline Hazard Functions ; 10.4.2. Censoring ; 10.4.3. Unobserved
Heterogeneity ; 10.5. Testing the SACPH Model.
Note continued: 10.6. Estimating Volatility Using the SACPH Model ; 10.6.1. Data and
the Generation of Price Events ; 10.6.2. Empirical Findings ; References ; 11.
Univariate Dynamic Intensity Models ; 11.1. The Autoregressive Conditional Intensity
Model ; 11.2. Generalized ACI Models ; 11.2.1. Long-Memory ACI Models ; 11.2.2.
An AFT-Type ACI Model ; 11.2.3.A Component ACI Model ; 11.2.4. Empirical Application
; 11.3. Hawkes Processes ; References ; 12. Multivariate Dynamic Intensity Models
; 12.1. Multivariate ACI Models ; 12.2. Applications of Multivariate ACI Models
; 12.2.1. Estimating Simultaneous Buy/Sell Intensities ; 12.2.2. Modelling Order
Aggressiveness ; 12.3. Multivariate Hawkes Processes ; 12.3.1. Statistical Properties
; 12.3.2. Estimating Multivariate Price Intensities ; 12.4. Stochastic Conditional
Intensity Processes ; 12.4.1. Model Structure ; 12.4.2. Probabilistic Properties
of the SCI Model ; 12.4.3. Statistical Inference.
Note continued: 12.5. SCI Modelling of Multivariate Price Intensities ; References
; 13. Autoregressive Discrete Processes and Quote Dynamics ; 13.1. Univariate Dynamic
Count Data Models ; 13.1.1. Autoregressive Conditional Poisson Models ; 13.1.2.
Extended ACP Models ; 13.1.3. Empirical Illustrations ; 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 ; 13.6.1. Cointegration Models for Ask
and Bid Quotes ; 13.6.2. Decomposing Quote Dynamics ; References ; A. Important
Distributions for Positive-Valued Data.