Econometrics of financial high-frequency data
By: Nikolaus Hautsch
Publisher: Springer
Published: 2012
Place of publication: Berlin
Language: eng
Number of pages: 371
ISBN-13: 9783642219245
Subjects: Foreign exchange rates; Econometric models; Finance; Econometrics
Notes: Includes bibliographical references and index.
Table of contents: title: Machine generated contents note: 1.Introduction; title: 1.1.Motivation; title: 1.2.Structure of the Book; title: References; title: 2.Microstructure Foundations; title: 2.1.The Institutional Framework of Trading; title: 2.1.1.Types of Traders and Forms of Trading; title: 2.1.2.Types of Orders; title: 2.1.3.Market Structures; title: 2.1.4.Order Precedence and Pricing Rules; title: 2.1.5.Trading Forms at Selected International Exchanges; title: 2.2.A Review of Market Microstructure Theory; title: 2.2.1.Asymmetric Information Based Models; title: 2.2.2.Inventory Models; title: 2.2.3.Major Implications for Trading Variables; title: 2.2.4.Models for Limit Order Book Markets; title: References; title: 3.Empirical Properties of High-Frequency Data; title: 3.1.Handling High-Frequency Data; title: 3.1.1.Databases and Trading Variables; title: 3.1.2.Matching Trades and Quotes; title: 3.1.3.Data Cleaning; title: 3.1.4.Split-Transactions; title: 3.1.5.Identification of Buyer- and Seller-Initiated Trades; title: 3.2.Aggregation by Trading Events: Financial Durations; title: Contents note continued: 3.2.1.Trade and Order Arrival Durations; title: 3.2.2.Price and Volume Durations; title: 3.3.Properties of Financial Durations; title: 3.4.Properties of Trading Characteristics; title: 3.5.Properties of Time Aggregated Data; title: 3.6.Summary of Major Empirical Findings; title: References; title: 4.Financial Point Processes; title: 4.1.Basic Concepts of Point Processes; title: 4.1.1.Fundamental Definitions; title: 4.1.2.Compensators and Intensities; title: 4.1.3.The Homogeneous Poisson Process; title: 4.1.4.Generalizations of Poisson Processes; title: 4.1.5.A Random Time Change Argument; title: 4.1.6.Intensity-Based Inference; title: 4.1.7.Simulation and Diagnostics; title: 4.2.Four Ways to Model Point Processes; title: 4.2.1.Intensity Models; title: 4.2.2.Hazard Models; title: 4.2.3.Duration Models; title: 4.2.4.Count Data Models; title: 4.3.Censoring and Time-Varying Covariates; title: 4.3.1.Censoring; title: 4.3.2.Time-Varying Covariates; title: 4.4.An Outlook on Dynamic Extensions; title: References; title: 5.Univariate Multiplicative Error Models; title: Contents note continued: 5.1.ARMA Models for Log Variables; title: 5.2.A MEM for Durations: The ACD Model; title: 5.3.Estimation of the ACD Model; title: 5.3.1.QML Estimation; title: 5.3.2.ML Estimation; title: 5.4.Seasonalities and Explanatory Variables; title: 5.5.The Log-ACD Model; title: 5.6.Testing the ACD Model; title: 5.6.1.Portmanteau Tests; title: 5.6.2.Independence Tests; title: 5.6.3.Distribution Tests; title: 5.6.4.Lagrange Multiplier Tests; title: 5.6.5.Conditional Moment Tests; title: 5.6.6.Monte Carlo Evidence; title: References; title: 6.Generalized Multiplicative Error Models; title: 6.1.A Class of Augmented ACD Models; title: 6.1.1.Special Cases; title: 6.1.2.Theoretical Properties; title: 6.1.3.Empirical Illustrations; title: 6.2.Regime-Switching ACD Models; title: 6.2.1.Threshold ACD Models; title: 6.2.2.Smooth Transition ACD Models; title: 6.2.3.Markov Switching ACD Models; title: 6.3.Long Memory ACD Models; title: 6.4.Mixture and Component Multiplicative Error Models; title: 6.4.1.The Stochastic Conditional Duration Model; title: 6.4.2.Stochastic Multiplicative Error Models; title: Contents note continued: 6.4.3.Component Multiplicative Error Models; title: 6.5.Further Generalizations of Multiplicative Error Models; title: 6.5.1.Competing Risks ACD Models; title: 6.5.2.Semiparametric ACD Models; title: 6.5.3.Stochastic Volatility Duration Models; title: References; title: 7.Vector Multiplicative Error Models; title: 7.1.VMEM Processes; title: 7.1.1.The Basic VMEM Specification; title: 7.1.2.Statistical Inference; title: 7.1.3.Applications; title: 7.2.Stochastic Vector Multiplicative Error Models; title: 7.2.1.Stochastic VMEM Processes; title: 7.2.2.Simulation-Based Inference; title: 7.2.3.Modelling Trading Processes; title: References; title: 8.Modelling High-Frequency Volatility; title: 8.1.Intraday Quadratic Variation Measures; title: 8.1.1.Maximum Likelihood Estimation; title: 8.1.2.The Realized Kernel Estimator; title: 8.1.3.The Pre-averaging Estimator; title: 8.1.4.Empirical Evidence; title: 8.1.5.Modelling and Forecasting Intraday Variances; title: 8.2.Spot Variances and Jumps; title: 8.3.Trade-Based Volatility Measures; title: Contents note continued: 8.4.Volatility Measurement Using Price Durations; title: 8.5.Modelling Quote Volatility; title: References; title: 9.Estimating Market Liquidity; title: 9.1.Simple Spread and Price Impact Measures; title: 9.1.1.Spread Measures; title: 9.1.2.Price Impact Measures; title: 9.2.Volume Based Measures; title: 9.2.1.The VNET Measure; title: 9.2.2.Excess Volume Measures; title: 9.3.Modelling Order Book Depth; title: 9.3.1.A Cointegrated VAR Model for Quotes and Depth; title: 9.3.2.A Dynamic Nelson; title: Siegel Type Order Book Model; title: 9.3.3.A Semiparametric Dynamic Factor Model; title: References; title: 10.Semiparametric Dynamic Proportional Hazard Models; title: 10.1.Dynamic Integrated Hazard Processes; title: 10.2.The Semiparametric ACPH Model; title: 10.3.Properties of the Semiparametric ACPH Model; title: 10.3.1.Autocorrelation Structure; title: 10.3.2.Estimation Quality; title: 10.4.Extended SACPH Models; title: 10.4.1.Regime-Switching Baseline Hazard Functions; title: 10.4.2.Censoring; title: 10.4.3.Unobserved Heterogeneity; title: 10.5.Testing the SACPH Model; title: Contents note continued: 10.6.Estimating Volatility Using the SACPH Model; title: 10.6.1.Data and the Generation of Price Events; title: 10.6.2.Empirical Findings; title: References; title: 11.Univariate Dynamic Intensity Models; title: 11.1.The Autoregressive Conditional Intensity Model; title: 11.2.Generalized ACI Models; title: 11.2.1.Long-Memory ACI Models; title: 11.2.2.An AFT-Type ACI Model; title: 11.2.3.A Component ACI Model; title: 11.2.4.Empirical Application; title: 11.3.Hawkes Processes; title: References; title: 12.Multivariate Dynamic Intensity Models; title: 12.1.Multivariate ACI Models; title: 12.2.Applications of Multivariate ACI Models; title: 12.2.1.Estimating Simultaneous Buy/Sell Intensities; title: 12.2.2.Modelling Order Aggressiveness; title: 12.3.Multivariate Hawkes Processes; title: 12.3.1.Statistical Properties; title: 12.3.2.Estimating Multivariate Price Intensities; title: 12.4.Stochastic Conditional Intensity Processes; title: 12.4.1.Model Structure; title: 12.4.2.Probabilistic Properties of the SCI Model; title: 12.4.3.Statistical Inference; title: Contents note continued: 12.5.SCI Modelling of Multivariate Price Intensities; title: References; title: 13.Autoregressive Discrete Processes and Quote Dynamics; title: 13.1.Univariate Dynamic Count Data Models; title: 13.1.1.Autoregressive Conditional Poisson Models; title: 13.1.2.Extended ACP Models; title: 13.1.3.Empirical Illustrations; title: 13.2.Multivariate ACP Models; title: 13.3.A Simple Model for Transaction Price Dynamics; title: 13.4.Autoregressive Conditional Multinomial Models; title: 13.5.Autoregressive Models for Integer-Valued Variables; title: 13.6.Modelling Ask and Bid Quote Dynamics; title: 13.6.1.Cointegration Models for Ask and Bid Quotes; title: 13.6.2.Decomposing Quote Dynamics; title: References; title: A.Important Distributions for Positive-Valued Data.