Author : United States. Presidential Task Force on Market Mechanisms
Publisher :
Page : 384 pages
File Size : 31,16 MB
Release : 1988
Category : Financial futures
ISBN :
Author : Maureen O'Hara
Publisher : John Wiley & Sons
Page : 310 pages
File Size : 47,37 MB
Release : 1998-03-06
Category : Business & Economics
ISBN : 0631207619
Written by one of the leading authorities in market microstructure research, this book provides a comprehensive guide to the theoretical work in this important area of finance.
Author : Ayan Bhattacharya
Publisher : CFA Institute Research Foundation
Page : 41 pages
File Size : 46,54 MB
Release : 2020-01-22
Category : Business & Economics
ISBN : 1944960929
Exchange-traded funds (ETFs) revolutionized asset markets by using an innovative structure to make investing in a wide variety of asset classes simpler and cheaper. With their growing importance has come increasing concern that these products pose new risks to market stability and performance. This paper examines whether ETFs affect systemic risks in financial markets and, if they do, what the mechanism is by which this impact occurs and what can be done to keep the risks under control. We review current research and empirical evidence on these issues and discuss some emerging risks in ETFs. We ask whether we have the right “rules of the road” to deal with the new drivers of market behavior.
Author : Robert J. Barro
Publisher : Irwin Professional Publishing
Page : 422 pages
File Size : 22,5 MB
Release : 1989
Category : Business & Economics
ISBN :
Author : Larry Harris
Publisher : OUP USA
Page : 664 pages
File Size : 29,85 MB
Release : 2003
Category : Business & Economics
ISBN : 9780195144703
Focusing on market microstructure, Harris (chief economist, U.S. Securities and Exchange Commission) introduces the practices and regulations governing stock trading markets. Writing to be understandable to the lay reader, he examines the structure of trading, puts forward an economic theory of trading, discusses speculative trading strategies, explores liquidity and volatility, and considers the evaluation of trader performance. Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com).
Author : H. Kent Baker
Publisher : John Wiley & Sons
Page : 758 pages
File Size : 16,66 MB
Release : 2013-07-31
Category : Business & Economics
ISBN : 1118421485
A comprehensive guide to the dynamic area of finance known as market microstructure Interest in market microstructure has grown dramatically in recent years due largely in part to the rapid transformation of the financial market environment by technology, regulation, and globalization. Looking at market transactions at the most granular level—and taking into account market structure, price discovery, information flows, transaction costs, and the trading process—market microstructure also forms the basis of high-frequency trading strategies that can help professional investors generate profits and/or execute optimal transactions. Part of the Robert W. Kolb Series in Finance, Market Microstructure skillfully puts this discipline in perspective and examines how the working processes of markets impact transaction costs, prices, quotes, volume, and trading behavior. Along the way, it offers valuable insights on how specific features of the trading process like the existence of intermediaries or the environment in which trading takes place affect the price formation process. Explore issues including market structure and design, transaction costs, information flows, and disclosure Addresses market microstructure in emerging markets Covers the legal and regulatory issues impacting this area of finance Contains contributions from both experienced financial professionals and respected academics in this field If you're looking to gain a firm understanding of market microstructure, this book is the best place to start.
Author : Monique Jeanblanc
Publisher : Springer Science & Business Media
Page : 754 pages
File Size : 47,45 MB
Release : 2009-10-03
Category : Business & Economics
ISBN : 1846287375
Mathematical finance has grown into a huge area of research which requires a large number of sophisticated mathematical tools. This book simultaneously introduces the financial methodology and the relevant mathematical tools in a style that is mathematically rigorous and yet accessible to practitioners and mathematicians alike. It interlaces financial concepts such as arbitrage opportunities, admissible strategies, contingent claims, option pricing and default risk with the mathematical theory of Brownian motion, diffusion processes, and Lévy processes. The first half of the book is devoted to continuous path processes whereas the second half deals with discontinuous processes. The extensive bibliography comprises a wealth of important references and the author index enables readers quickly to locate where the reference is cited within the book, making this volume an invaluable tool both for students and for those at the forefront of research and practice.
Author : United States. Congress. Senate. Committee on Banking, Housing, and Urban Affairs. Subcommittee on Securities
Publisher :
Page : 164 pages
File Size : 31,48 MB
Release : 1999
Category : Business & Economics
ISBN :
Author : Antoine Bouveret
Publisher : International Monetary Fund
Page : 44 pages
File Size : 45,66 MB
Release : 2015-10-13
Category : Business & Economics
ISBN : 1513576224
Changes in the structure of the U.S. Treasury market over recent years may have increased risks to financial stability. Traditional market makers have changed their liquidity provision by increasingly switching from risk warehousing to risk distribution, and a new breed of market maker has emerged with the rise of electronic trading. The “flash rally” of October 15, 2014 provides a clear example of how those risks can materialize. Based on an in-depth analysis of the event—complementing the authorities’ work—we suggest i) providing incentives for liquidity provision, ii) improving market safeguards, and iii) enhancing the regulation of the Treasury market.
Author : Matthew F. Dixon
Publisher : Springer Nature
Page : 565 pages
File Size : 15,7 MB
Release : 2020-07-01
Category : Business & Economics
ISBN : 3030410684
This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.
