Fr. 69.00

Market Microstructure - Confronting Many Viewpoints

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Informationen zum Autor FRÉDÉRIC ABERGEL graduated from École Normale Supérieure with a PhD in Mathematics. He started an academic career as a researcher with the CNRS. He spent ten years in the Mathematics department of the University of Orsay Paris XI and then switched to the capital markets industry and became a quantitative analyst. He has worked for trading floors in various financial institutions! mainly in the derivatives sector! developing pricing and hedging models. He now holds the BNP Paribas Chair of Quantitative Finance at École Centrale Paris. His research focuses on the study of empirical properties and mathematical models of market microstructure! high frequency data! algorithmic trading.JEAN-PHILIPPE BOUCHAUD graduated from the École Normale Supérieure in Paris! where he also obtained his PhD in physics. He was then appointed by the CNRS. After a year spent in the Cavendish Laboratory! he joined the Service de Physique de l'Etat Condensé! where he worked on the dynamics of glassy systems and on granular media. His work in finance includes extreme risk models! agent based simulations! market microstructure and price formation. He went on to found the company Science & Finance that merged with Capital Fund Management. He is now the President and Head of Research at CFM! and professor at École Polytechnique. He has published over 250 scientific papers and several books in physics and in finance.THIERRY FOUCAULT is Professor of Finance at HEC! Paris where he received his PhD in Finance. He is a research fellow of the Centre for Economic Policy. His research focuses on the determinants of financial markets liquidity and the industrial organization of the securities industry. His work has been published in top-tier scientific journals! including the Journal of Finance! the Journal of Financial Economics! and the Review of Financial Studies. He acts as co-editor of the Review of Finance and he is an Associate Editor of the Review of Asset Pricing Studies. For his research! he received awards from the Europlace Institute of Finance in 2005 and 2009! the annual research prize of the HEC Foundation in 2006 and 2009! and the Analysis Group award for the best paper on Financial Markets and Institutions presented at the 2009 Western Finance Association meetings.CHARLES-ALBERT LEHALLE is the Head of Quantitative Research at CA Cheuvreux and is an international expert in optimal trading. He published papers in international journals about the use of stochastic control and stochastic algorithms to optimise a trading flow with respect to flexible contraints. He also authored papers on post trade analysis! market impact estimates and modelling the dynamics of limit order books. He lectures at Paris 6 (El Karoui) Master of Finance (École Polytechnique! ESSEC! École Normale Supérieure) and MASEF/ENSAE! and gives master classes in the Certificate in Quantitative Finance in London. He holds a PhD in Applied Mathematics and his core fields are stochastic processes! information theory and nonlinear control.MATHIEU ROSENBAUM gained is PhD from University Paris-Est. He is now Professor at University Pierre et Marie Curie (Paris 6) and École Polytechnique and is a member of the CREST (Center of Research in Economics and Statistics). His research mainly focuses on statistical finance problems! such as market microstructure modeling or designing statistical procedures for high frequency data. He also has research collaborations with several financial institutions! in particular BNP Paribas. Klappentext The latest cutting-edge research on market microstructureBased on the December 2010 conference on market microstructure! organized with the help of the Institut Louis Bachelier! this guide brings together the leading thinkers to discuss this important field of modern finance. It provides readers with vital insight on the origin of the well-known anomalous "stylized facts" in financial prices series! n...

List of contents

IntroductionAbout the EditorsPART I ECONOMIC MICROSTRUCTURE THEORY1 Algorithmic Trading: Issues and Preliminary EvidenceThierry Foucault1.1 Introduction1.2 What is algorithmic trading?1.2.1 Definition and typology1.2.2 Scope and profitability1.3 Market structure and algorithmic trading1.4 Costs and benefits of algorithmic trading1.4.1 Algorithmic trading reduces search costs1.4.2 Algorithmic trading has an ambiguous effect on adverse selection costs1.4.3 Algorithmic trading and price discovery1.4.4 Welfare effects1.4.5 Algorithmic trading as a source of risk1.5 Empirical evidence1.5.1 Algorithmic trading and market liquidity1.5.2 Algorithmic trading and volatility1.5.3 Algorithmic trading and price discovery1.5.4 Algorithmic trading and market stability1.6 ConclusionsAppendixAcknowledgmentReferences2 Order Choice and Information in Limit Order Markets 41Ioanid Rou2.1 Introduction2.2 Order choice with symmetric information2.3 Order choice with asymmetric information2.4 The information content of orders2.5 Questions for future researchReferencesPART II HIGH FREQUENCY DATA MODELING3 Some Recent Results on High Frequency CorrelationNicolas Huth and Frédéric Abergel3.1 Introduction3.2 Data description3.3 Multivariate event time3.3.1 Univariate case3.3.2 Multivariate case3.3.3 Empirical results3.4 High frequency lead/lag3.4.1 The Hayashi-Yoshida cross-correlation function3.4.2 Empirical results3.5 Intraday seasonality of correlation3.5.1 Empirical results3.6 ConclusionAcknowledgmentReferences4 Statistical Inference for Volatility and Related Limit TheoremsNakahiro Yoshida4.1 Introduction4.2 QLA for an ergodic diffusion process4.3 QLA for volatility in the finite time-horizon4.4 Nonsynchronous covariance estimation4.4.1 Consistent estimator4.4.2 Functional limit theorem4.4.3 Application of YUIMA4.4.4 Lead-lag estimation4.5 YUIMA II for statistical analysis and simulation for stochastic differential equations4.6 Higher order asymptotics and finance4.6.1 Martingale expansion4.6.2 Small sigma expansionAcknowledgmentsReferencesPART III MARKET IMPACT5 Models for the Impact of All Order Book EventsZoltán Eisler, Jean-Philippe Bouchaud, and Julien Kockelkoren5.1 Introduction5.2 A short summary of market order impact models5.3 Many-event impact models5.3.1 Notation and definitions5.3.2 The transient impact model (TIM)5.3.3 The history dependent impact model (HDIM)5.4 Model calibration and empirical tests5.4.1 Data5.4.2 The case of large ticks5.4.3 The case of small ticks5.5 ConclusionAppendixAcknowledgmentsReferences6 Limit Order Flow, Market Impact, and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH DataNikolaus Hautsch and Ruihong Huang6.1 Introduction6.2 Market environment and data6.3 Major order flow and order book characteristics6.4 An econometric model for the market impact of limit orders6.4.1 A cointegrated VAR model for the limit order book6.4.2 Estimating market impact6.5 Market impact at NASDAQ6.6 Optimal order size6.7 ConclusionsAcknowledgmentReferencesPART IV OPTIMAL TRADINGIntroduction: Trading and Market Micro-structureCharles-Albert LehalleReferences7 Collective Portfolio Optimization in Brokerage Data: The Role of Transaction Cost StructureDamien Challet and David Morton de Lachapelle7.1 Introduction7.2 Description of the data7.3 Results7.4 The influence of transaction costs on trading behaviour from optimal mean-variance portfolios7.5 Discussion and outlookAcknowledgmentsReferences8 Optimal Execution of Portfolio Transactions with Short-Term AlphaAdriana M. Criscuolo and Henri Waelbroeck8.1 Introduction8.2 Short-term alpha decay and hidden order arbitrage theory8.3 Total cost definition and constraints8.3.1 Equations without the risk term8.3.2 Equations including risk without the alpha term8.4 Total cost optimization8.4.1 Results for lambda = 0 and the arbitrary alpha term8.4.2 Risk-adjusted optimization8.5 Conclusions8.5.1 Main results in the absence of short-term alpha8.5.2 Main results with short-term alpha8.5.3 Institutional trading practicesProvisoReferencesCombined ReferencesIndex

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