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Market microstructure : confronting many viewpoints /
The latest cutting-edge research on market microstructure Based 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 wi...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, N.J. :
Wiley,
2012.
|
| Colección: | The Wiley finance series
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Market microstructure : |b confronting many viewpoints / |c edited by Frédéric Abergel [and others]. |
| 260 | |a Hoboken, N.J. : |b Wiley, |c 2012. | ||
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 0 | |a The Wiley finance series | |
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record and CIP data provided by publisher. | |
| 505 | 0 | |a Cover; Series; Title Page; Copyright; Introduction; About the Editors; Part I: Economic Microstructure Theory; 1: Algorithmic Trading: Issues and Preliminary Evidence; 1.1 INTRODUCTION; 1.2 WHAT IS ALGORITHMIC TRADING?; 1.3 MARKET STRUCTURE AND ALGORITHMIC TRADING; 1.4 COSTS AND BENEFITS OF ALGORITHMIC TRADING; 1.5 EMPIRICAL EVIDENCE; 1.6 CONCLUSIONS; 1.7 APPENDIX; ACKNOWLEDGMENT; 2: Order Choice and Information in Limit Order Markets; 2.1 INTRODUCTION; 2.2 ORDER CHOICE WITH SYMMETRIC INFORMATION; 2.3 ORDER CHOICE WITH ASYMMETRIC INFORMATION; 2.4 THE INFORMATION CONTENT OF ORDERS. | |
| 520 | |a The latest cutting-edge research on market microstructure Based 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, namely heavy tails, volatility, and clustering, and illustrates their impact on the organization of markets, execution costs, price impact, organization liquidity in electronic markets, and other. | ||
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| 650 | 0 | |a Securities. | |
| 650 | 0 | |a Securities |x Prices. | |
| 650 | 0 | |a Stock exchanges. | |
| 650 | 0 | |a Microfinance. | |
| 650 | 6 | |a Valeurs mobilières |x Prix. | |
| 650 | 6 | |a Bourse. | |
| 650 | 7 | |a stock exchanges. |2 aat | |
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| 650 | 7 | |a Securities |2 fast | |
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| 700 | 1 | |a Abergel, Frédéric. | |
| 758 | |i has work: |a Market microstructure (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGKdMgqfbHkgHm76f99TRC |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |t Market microstructure. |d Hoboken, N.J. : Wiley, 2012 |z 9781119952411 |w (DLC) 2012002916 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=818553 |z Texto completo |
| 880 | 0 | 0 | |6 505-00/(S |g Part I. |t Economic Microstructure Theory -- -- |g 1. |t Algorithmic Trading: Issues and Preliminary Evidence -- |g 1.1. |t Introduction -- |g 1.2. |t What is algorithmic trading-- |g 1.2.1. |t Definition and typology -- |g 1.2.2. |t Scope and profitability -- |g 1.3. |t Market structure and algorithmic trading -- |g 1.4. |t Costs and benefits of algorithmic trading -- |g 1.4.1. |t Algorithmic trading reduces search costs -- |g 1.4.2. |t Algorithmic trading has an ambiguous effect on adverse selection costs -- |g 1.4.3. |t Algorithmic trading and price discovery -- |g 1.4.4. |t Welfare effects -- |g 1.4.5. |t Algorithmic trading as a source of risk -- |g 1.5. |t Empirical evidence -- |g 1.5.1. |t Algorithmic trading and market liquidity -- |g 1.5.2. |t Algorithmic trading and volatility -- |g 1.5.3. |t Algorithmic trading and price discovery -- |g 1.5.4. |t Algorithmic trading and market stability -- |g 1.6. |t Conclusions -- -- |g 2. |t Order Choice and Information in Limit Order Markets -- |g 2.1. |t Introduction -- |g 2.2. |t Order choice with symmetric information -- |g 2.3. |t Order choice with asymmetric information -- |g 2.4. |t The information content of orders -- |g 2.5. |t Questions for future research -- -- |g Part II. |t High Frequency Data Modeling -- -- |g 3. |t Some Recent Results on High Frequency Correlation -- |g 3.1. |t Introduction -- |g 3.2. |t Data description -- |g 3.3. |t Multivariate event time -- |g 3.3.1. |t Univariate case -- |g 3.3.2. |t Multivariate case -- |g 3.3.3. |t Empirical results -- |g 3.4. |t High frequency lead/lag -- |g 3.4.1. |t The Hayashi-Yoshida cross-correlation function -- |g 3.4.2. |t Empirical results -- |g 3.5. |t Intraday seasonality of correlation -- |g 3.5.1. |t Empirical results -- |g 3.6. |t Conclusion -- -- |g 4. |t Statistical Inference for Volatility and Related Limit Theorems -- |g 4.1. |t Introduction -- |g 4.2. |t QLA for an ergodic diffusion process -- |g 4.3. |t QLA for volatility in the finite time-horizon -- |g 4.4. |t Nonsynchronous covariance estimation -- |g 4.4.1. |t Consistent estimator -- |g 4.4.2. |t Functional limit theorem -- |g 4.4.3. |t Application of YUIMA -- |g 4.4.4. |t Lead-lag estimation -- |g 4.5. |t YUIMA II for statistical analysis and simulation for stochastic differential equations -- |g 4.6. |t Higher order asymptotics and finance -- |g 4.6.1. |t Martingale expansion -- |g 4.6.2. |t Small σ expansion -- -- |g Part III. |t Market Impact -- -- |g 5. |t Models for the Impact of All Order Book Events -- |g 5.1. |t Introduction -- |g 5.2. |t A short summary of market order impact models -- |g 5.3. |t Many-event impact models -- |g 5.3.1. |t Notation and definitions -- |g 5.3.2. |t The transient impact model (TIM) -- |g 5.3.3. |t The history dependent impact model (HDIM) -- |g 5.4. |t Model calibration and empirical tests -- |g 5.4.1. |t Data -- |g 5.4.2. |t The case of large ticks -- |g 5.4.3. |t The case of small ticks -- |g 5.5. |t Conclusion -- -- |g 6. |t Limit Order Flow, Market Impact, and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data -- |g 6.1. |t Introduction -- |g 6.2. |t Market environment and data -- |g 6.3. |t Major order flow and order book characteristics -- |g 6.4. |t An econometric model for the market impact of limit orders -- |g 6.4.1. |t A cointegrated VAR model for the limit order book -- |g 6.4.2. |t Estimating market impact -- |g 6.5. |t Market impact at NASDAQ -- |g 6.6. |t Optimal order size -- |g 6.7. |t Conclusions -- -- |g Part IV. |t Optimal Trading -- -- |g 7. |t Collective Portfolio Optimization in Brokerage Data: The Role of Transaction Cost Structure -- |g 7.1. |t Introduction -- |g 7.2. |t Description of the data -- |g 7.3. |t Results -- |g 7.4. |t The influence of transaction costs on trading behavior from optimal mean-variance portfolios -- |g 7.5. |t Discussion and outlook -- -- |g 8. |t Optimal Execution of Portfolio Transactions with Short-Term Alpha -- |g 8.1. |t Introduction -- |g 8.2. |t Short-term alpha decay and hidden order arbitrage theory -- |g 8.3. |t Total cost definition and constraints -- |g 8.3.1. |t Equations without the risk term -- |g 8.3.2. |t Equations including risk without the alpha term -- |g 8.4. |t Total cost optimization -- |g 8.4.1. |t Results for λ = 0 and the arbitrary alpha term -- |g 8.4.2. |t Risk-adjusted optimization -- |g 8.5. |t Conclusions -- |g 8.5.1. |t Main results in the absence of short-term alpha -- |g 8.5.2. |t Main results with short-term alpha -- |g 8.5.3. |t Institutional trading practices. |
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