Modelling Irregularly Spaced Financial Data

Transcription

1 Nikolaus Hautsch Modelling Irregularly Spaced Financial Data Theory and Practice of Dynamic Duration Models Springer C

2 Contents Introduction 1 Point Processes Basic Concepts of Point Processes Fundamental Definitions The Homogeneous Poisson Process The Intensity Function and its Properties Intensity-Based Inference Types of Point Processes Poisson Processes Renewal Processes Dynamic Point Processes Non-Dynamic Point Process Models Intensity-Based Models Duration Models Count Data Models Censoring and Time-Varying Covariates Censoring Time-Varying Covariates Outlook on Dynamic Extensions 28 Economic Implications of Financial Durations Types of Financial Durations Selection by Single Marks Selection by Sequences of Marks The Role of Trade Durations in Market Microstructure Theory Traditional Market Microstructure Approaches Determinants of Trade Durations Risk Estimation based on Price Durations Duration-Based Volatility Measurement Economic Implications of Directional Change Durations 42

3 X Contents 3.4 Liquidity Measurement The Liquidity Concept Volume Durations and Liquidity The VNET Measure Measuring (II)liquidity Risks using Excess Volume Durations 44 4 Statistical Properties of Financial Durations Data Preparation Issues Matching Trades and Quotes Treatment of Split-Transactions Identification of Buyer- and Seller-Initiated Trades Transaction Databases and Data Preparation NYSE Trading XETRA Trading Frankfurt Floor Trading Bund Future Trading at EUREX and.liffe ASX Trading Statistical Properties of Trade, Limit Order and Quote Durations Statistical Properties of Price Durations Statistical Properties of (Excess) Volume Durations Summarizing the Statistical Findings 75 5 Autoregressive Conditional Duration Models ARMA Models for (Log-)Durations The ACD Model The Basic ACD Framework QML Estimation of the ACD Model Distributional Issues and ML Estimation of the ACD Model ' Seasonalities and Explanatory Variables Extensions of the ACD Framework Augmented ACD Models Theoretical Properties of Augmented ACD Models Regime-Switching ACD Models, Long Memory ACD Models Further Extensions Testing the ACD Model Simple Residual Checks Density Forecast Evaluations Lagrange Multiplier Tests Conditional Moment Tests Integrated Conditional Moment Tests Monte Carlo Evidence 115

4 Contents XI 5.5. Applications of ACD Models : Evaluating ACD Models based on Trade and Price Durations Modelling Trade Durations Quantifying (Il)liquidity Risks Semiparametric Dynamic Proportional Intensity Models Dynamic Integrated Intensity Processes The Semiparametric ACPI Model Properties of the Semiparametric ACPI Model Autocorrelation Structure Evaluating the Estimation Quality Extensions of the ACPI Model Regime-Switching Dynamics Regime-Switching Baseline Intensities Censoring Unobserved Heterogeneity Testing the ACPI Model Estimating Volatility Using the ACPI Model The Data and the Generation of Price Events Empirical Findings Univariate and Multivariate Dynamic Intensity Models Univariate Dynamic Intensity Models The ACI Model The Hawkes Model Multivariate Dynamic Intensity Models Definitions The Multivariate ACI Model The Multivariate Hawkes Model Dynamic Latent Factor Models for Intensity Processes The LFI Model The Univariate LFI Model The Multivariate LFI Model Dynamic Properties of the LFI Model SML Estimation of the LFI Model Testing the LFI Model Applications of Dynamic Intensity Models Estimating Multivariate Price Intensities Estimating Simultaneous Buy/Sell Intensities Estimating Trading Intensities Using LFI Models Summary and Conclusions 255 A Important Distributions for Duration Data 259

5 XII Contents B List of Symbols (in Alphabetical Order) 265 References 273 Index 285