Dissertation Information Asymmetry and Information Dissemination in High- Frequency Capital Markets Thomas Pöppe Dissertation Vom Fachbereich für Rechts- und Wirtschaftswissenschaften, Technische Universität Darmstadt (D17) zur Erlangung des akademischen Grades Doctor rerum politicarum (Dr. rer. pol.) genehmigte Dissertation Information Asymmetry and Information Dissemination in High-Frequency Capital Markets vorgelegt von Dipl.-Wirtsch.-Inf. Thomas Pöppe geboren in Frankfurt, Deutschland Einreichungsdatum: 03.06.2015 Datum der mündlichen Prüfung: 15.10.2015 Erstgutachter: Prof. Dr. Dirk Schiereck Zweitgutachter: Prof. Dr. Alexander Benlian Darmstadt, 2016 Please cite this document as: Pöppe, Thomas: “Information Asymmetry and Information Dissemination in High- Frequency Capital Markets” Technische Universität Darmtadt, Diss., 2015. URN: urn:nbn:de:tuda-tuprints-53540 URL: http://tuprints.ulb.tu-darmstadt.de/id/eprint/5354 This document is provided by tuprints, E-Publishing-Service of TU Darmstadt. http://tuprints.ulb.tu-darmstadt.de [email protected] I Overview Table of Contents ......................................................................................................... II List of Tables ............................................................................................................... V List of Tables in Appendix ......................................................................................... VII List of Figures .......................................................................................................... VIII List of Abbreviations and Frequently Used Symbols ................................................... IX 1 Introduction ........................................................................................................... 1 2 The Microstructure Trading Model by Easley et al. (1997) ..................................... 6 2.1 The trading process and market participants .................................................... 6 2.2 Estimation of model parameters and PIN ........................................................ 9 2.3 Discussion of key assumptions ...................................................................... 11 2.4 The context of the EKO models .................................................................... 13 2.5 Summary ...................................................................................................... 19 3 The Intraday Probability of Informed Trading ...................................................... 21 3.1 Introduction .................................................................................................. 21 3.2 An updated estimation procedure for PIN ..................................................... 24 3.3 Research design ............................................................................................ 27 3.4 Data and descriptive statistics ....................................................................... 33 3.5 Empirical results ........................................................................................... 37 3.6 Conclusion .................................................................................................... 61 4 The Sensitivity of VPIN to the Choice of Trade Classification Algorithm ............ 63 4.1 Introduction .................................................................................................. 63 4.2 Trade classification algorithms and their performance ................................... 66 4.3 Research design ............................................................................................ 74 4.4 Data .............................................................................................................. 81 4.5 Results .......................................................................................................... 83 4.6 Conclusion .................................................................................................. 105 5 Information or Noise: Does Twitter Facilitate Information Dissemination? ........ 107 5.1 Introduction ................................................................................................ 107 5.2 Related literature and hypothesis ................................................................. 109 5.3 Research design .......................................................................................... 113 5.4 Sample composition and descriptives .......................................................... 117 5.5 Results ........................................................................................................ 134 5.6 Conclusion .................................................................................................. 151 6 Overall Summary and Conclusion ...................................................................... 154 References ................................................................................................................ 161 Appendix .................................................................................................................. 169 II Table of Contents Table of Contents ......................................................................................................... II List of Tables ............................................................................................................... V List of Tables in Appendix ......................................................................................... VII List of Figures .......................................................................................................... VIII List of Abbreviations and Frequently Used Symbols ................................................... IX 1 Introduction ........................................................................................................... 1 2 The Microstructure Trading Model by Easley et al. (1997) ..................................... 6 2.1 The trading process and market participants .................................................... 6 2.2 Estimation of model parameters and PIN ........................................................ 9 2.3 Discussion of key assumptions ...................................................................... 11 2.4 The context of the EKO models .................................................................... 13 2.4.1 Earlier models ........................................................................................ 13 2.4.2 Innovations in PIN methodology ............................................................ 15 2.5 Summary ...................................................................................................... 19 3 The Intraday Probability of Informed Trading ...................................................... 21 3.1 Introduction .................................................................................................. 21 3.2 An updated estimation procedure for PIN ..................................................... 24 3.3 Research design ............................................................................................ 27 3.3.1 Robustness tests ..................................................................................... 29 3.3.2 Event study with ad-hoc announcements ................................................ 32 3.4 Data and descriptive statistics ....................................................................... 33 3.4.1 Trading data ........................................................................................... 33 3.4.2 Buy/sell classification ............................................................................ 35 3.4.3 Ad-hoc announcements .......................................................................... 36 3.5 Empirical results ........................................................................................... 37 3.5.1 Maximum likelihood estimation and robustness of parameters ............... 37 3.5.2 Event study with ad-hoc announcements ................................................ 46 3.5.3 Robustness tests ..................................................................................... 54 3.6 Conclusion .................................................................................................... 61 4 The Sensitivity of VPIN to the Choice of Trade Classification Algorithm ............ 63 III 4.1 Introduction .................................................................................................. 63 4.2 Trade classification algorithms and their performance ................................... 66 4.2.1 Trade-by-Trade classification algorithms ............................................... 66 4.2.2 Bulk classification ................................................................................. 68 4.2.3 Performance of traditional trade classification algorithms ...................... 69 4.2.4 Evaluation of bulk volume classification and VPIN ............................... 71 4.3 Research design ............................................................................................ 74 4.3.1 The Volume Synchronized Probability of Informed Trading (VPIN) ...... 74 4.3.2 Evaluation of the sensitivity of VPIN ..................................................... 76 4.4 Data .............................................................................................................. 81 4.5 Results .........................................................................................................