Market Microstructure in Practice [1 ed.]
Author(s)：Charles-Albert Lehalle, Sophie Laruelle
Publisher：World Scientific Publishing Company
Year：2013     Pages：332


Contents
About the Editors ...............v
About the Contributors ...............vii
Foreword by ...............xv
Robert Almgren........................ xv
Bertrand Patillet........................ xvi
Philippe Guillot ........................ xvii
Albert J. Menkveld ...................... xix
Preface by............... xxi
Charles-Albert Lehalle .................... xxi
Sophie Laruelle ........................ xxiv
Introduction ...............1
1. Monitoring the Fragmentation at Any Scale ...............29
1.1 Fluctuations of Market Shares: AFirst Graph on Liquidity ....................... 29
    1.1.1 The market share: Anot so obvious liquidity metric....................... 29
    1.1.2 Phase 1: First attempts of fragmentation . . ................ 34
    1.1.3 Phase 2: Convergence towards a European offer........................ 44
    1.1.4 Phase 3: Apparition of broker crossing networks and Dark Pools ........... 49
1.2 Smart Order Routing (SOR), AStructural Component of European Price Formation Process......... 56
    1.2.1 How to route orders in a fragmented market?............... 56
    1.2.2 Fragmentation is a consequence of primary markets’ variance................ 64
1.3 Still Looking for the Optimal Tick Size ........ 67
    1.3.1 Why does tick size matter?........... 67
    1.3.2 How tick size affects market quality ..... 70
    1.3.3 How can tick size be used by trading venue to earn market share? ............... 84
    1.3.4 How does tick size change the profitability of the various participants in the market? .... 90
    1.3.5 The value of a quote .............. 92
1.4 Can We See in the Dark? ................ 94
    1.4.1 Mechanism of dark liquidity pools ...... 95
    1.4.2 In-depth analysis of dark liquidity ...... 97
2. Understanding theStakes and theRoots of Fragmentation ...............109
2.1 From Intraday Market Share to Volume Curves: Some Stationarity Issues ................ 109
    2.1.1 Inventory-driven investors need fixing auctions ..................... 111
    2.1.2 Timing is money: Investors need to trade accordingly ................... 121
    2.1.3 Fragmentation and the evolution of intraday volume patterns................. 131
2.2 Does More Liquidity Guarantee a Better Market Share? ALittle Story About the European Bid-Ask Spread .......................... 134
    2.2.1 The bid-ask spread and volatility move accordingly ................... 136
    2.2.2 Bid-ask spread and market share are deeply linked ....................... 139
    2.2.3 Exchanges need to show volatility-resistance 142
2.3 The Agenda of High Frequency Traders: How Do They Extend their Universe?.............. 144
    2.3.1 Metrics for the balance in liquidity among indexes ...................... 145
    2.3.2 Ahistory of coverage .............. 147
    2.3.3 High-frequency traders do not impact all investors equally ................ 149
2.4 The Link Between Fragmentation and Systemic Risk 155
    2.4.1 The Spanish experiment ............ 155
    2.4.2 Volatility, cross-stock correlation, intraday, extraday ..................... 160
    2.4.3 The Flash Crash (May 6th, 2010) in NY: How far are we from systemic risk? ......... 173
3. Optimal Organisations for Optimal Trading ...............185
3.1 Organising a Trading Structure toAnswer to a Fragmented Landscape .............. 185
    3.1.1 Main inputs of trading tools .......... 186
    3.1.2 Components of trading algorithms ...... 189
    3.1.3 Main outputs of an automated trading system 190
3.2 Market Impact Measurements: Understanding the Price Formation Process from the Viewpoint of One               
      Investor .......................... 195
    3.2.1 Better understanding on what impacts the price ..................... 196
    3.2.2 Market impact over the trading period.... 197
    3.2.3 Market impact on a longer horizon: Different patterns for different investment styles.... 200
    3.2.4 Dependence between investment style and market impact on a monthly horizon..... 203
3.3 Optimal Trading Methods ............... 205
    3.3.1 Algorithmic trading: Adapting trading style to investors’ needs ............... 205
    3.3.2 Liquidity seeking algorithms are no longer nice to have ................... 210
Appendix A: Quantitative Appendix ...............221
A.1 From Entropy to FEI (Fragmentation Efficiency Index) ......................... 221
A.2 Information Seeking and Price Discovery..... 225
A.3 A Simple Model Explaining the Natural Fragmentation of Market Microstructure ..... 229
    A.3.1 A toy model of SOR dynamics . . . 229
    A.3.2 A toy model of the impact of SOR activity on the market shares.... 231
    A.3.3 A coupled model of SOR-market shares dynamics ........... 232
    A.3.4 Simulations.............. 232
    A.3.5 Qualitative analysis......... 233
A.4 AToy Model of the Flash Crash........... 235
    A.4.1 Amarket depth-oriented model . . 235
    A.4.2 Impact of the Flash Crash on our model................. 237
A.5 Harris Model: Underlying Continuous Spread Discretized by Tick.................. 240
    Motivation and notations......... 240
    Numerical application........... 243
A.6 Optimal Trade Scheduling.............. 247
    A.6.1 The trading model.......... 248
    A.6.2 Towards a mean-variance optimal trade scheduling ........... 249
A.7 Estimation of Proportion and its Confidence Intervals ........................ 255
    A.7.1 Application to the estimation of the market share of venues on an asset 256
    A.7.2 Aggregation or application to the market share on an index...... 256
    A.7.3 Comparison of the estimators . . . 257
A.8 Gini Coefficient and Kolmogorov-Smirnov Test . . 259
    A.8.1 Gini coefficient............ 259
    A.8.2 Kolmogorov-Smirnov test ..... 260
    A.8.3 Practical implementation...... 261
A.9 Simple Linear Regression Model.......... 264
    A.9.1 Model presentation......... 265
    A.9.2 Application to relation between spread and volatility ........ 266
A.10 Time Series and Seasonalities............ 270
    A.10.1 Introduction to time series..... 270
    A.10.2 Example of volume model..... 274
A.11 Clusters of Liquidity................. 276
    A.11.1 Introduction to point processes . . 276
    A.11.2 One-dimensional Hawkes processes 279
A.12 Signature Plot and Epps Effect ........... 283
    A.12.1 Volatility and signature plot.... 283
    A.12.2 Correlation and Epps effect .... 284
A.13 Averaging Effect.................... 286
    A.13.1 Mean versus path.......... 286
    A.13.2 Regression of average quantities versus mean of the regressions . . 286
Appendix B: Glossary............289
Bibliography ............297
Index ............303