The Science of Algorithmic Trading and Portfolio Management Book

The Science of Algorithmic Trading and Portfolio Management


  • Author : Robert Kissell
  • Publisher : Academic Press
  • Release Date : 2013-10-01
  • Genre: Business & Economics
  • Pages : 496
  • ISBN 10 : 9780124016934

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The Science of Algorithmic Trading and Portfolio Management Excerpt :

The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems. This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects. Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers. Helps readers design systems to manage algorithmic risk and dark pool uncertainty. Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.

Algorithmic Trading Methods Book

Algorithmic Trading Methods


  • Author : Robert L. Kissell
  • Publisher : Academic Press
  • Release Date : 2020-09-08
  • Genre: Business & Economics
  • Pages : 612
  • ISBN 10 : 9780128156315

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Algorithmic Trading Methods Excerpt :

Algorithmic Trading Methods: Applications using Advanced Statistics, Optimization, and Machine Learning Techniques, Second Edition, is a sequel to The Science of Algorithmic Trading and Portfolio Management. This edition includes new chapters on algorithmic trading, advanced trading analytics, regression analysis, optimization, and advanced statistical methods. Increasing its focus on trading strategies and models, this edition includes new insights into the ever-changing financial environment, pre-trade and post-trade analysis, liquidation cost & risk analysis, and compliance and regulatory reporting requirements. Highlighting new investment techniques, this book includes material to assist in the best execution process, model validation, quality and assurance testing, limit order modeling, and smart order routing analysis. Includes advanced modeling techniques using machine learning, predictive analytics, and neural networks. The text provides readers with a suite of transaction cost analysis functions packaged as a TCA library. These programming tools are accessible via numerous software applications and programming languages. Provides insight into all necessary components of algorithmic trading including: transaction cost analysis, market impact estimation, risk modeling and optimization, and advanced examination of trading algorithms and corresponding data requirements. Increased coverage of essential mathematics, probability and statistics, machine learning, predictive analytics, and neural networks, and applications to trading and finance. Advanced multiperiod trade schedule optimization and portfolio construction techniques. Techniques to decode broker-dealer and third-party vendor models. Methods to incorporate TCA into proprietary alpha models and portfolio optimizers. TCA library for numerous software applications and programming languages including: MATLAB, Excel Add-In, Python, Java, C/C++, .Net, Hadoop, and as standalone .EXE and .COM applications.

Quantitative Portfolio Management Book

Quantitative Portfolio Management


  • Author : Michael Isichenko
  • Publisher : John Wiley & Sons
  • Release Date : 2021-09-10
  • Genre: Business & Economics
  • Pages : 304
  • ISBN 10 : 9781119821212

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Quantitative Portfolio Management Excerpt :

Discover foundational and advanced techniques in quantitative equity trading from a veteran insider In Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage, distinguished physicist-turned-quant Dr. Michael Isichenko delivers a systematic review of the quantitative trading of equities, or statistical arbitrage. The book teaches you how to source financial data, learn patterns of asset returns from historical data, generate and combine multiple forecasts, manage risk, build a stock portfolio optimized for risk and trading costs, and execute trades. In this important book, you’ll discover: Machine learning methods of forecasting stock returns in efficient financial markets How to combine multiple forecasts into a single model by using secondary machine learning, dimensionality reduction, and other methods Ways of avoiding the pitfalls of overfitting and the curse of dimensionality, including topics of active research such as “benign overfitting” in machine learning The theoretical and practical aspects of portfolio construction, including multi-factor risk models, multi-period trading costs, and optimal leverage Perfect for investment professionals, like quantitative traders and portfolio managers, Quantitative Portfolio Management will also earn a place in the libraries of data scientists and students in a variety of statistical and quantitative disciplines. It is an indispensable guide for anyone who hopes to improve their understanding of how to apply data science, machine learning, and optimization to the stock market.

Statistical Arbitrage Book

Statistical Arbitrage


  • Author : Andrew Pole
  • Publisher : John Wiley & Sons
  • Release Date : 2011-07-07
  • Genre: Business & Economics
  • Pages : 230
  • ISBN 10 : 9781118160732

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Statistical Arbitrage Excerpt :

While statistical arbitrage has faced some tough times?as markets experienced dramatic changes in dynamics beginning in 2000?new developments in algorithmic trading have allowed it to rise from the ashes of that fire. Based on the results of author Andrew Pole?s own research and experience running a statistical arbitrage hedge fund for eight years?in partnership with a group whose own history stretches back to the dawn of what was first called pairs trading?this unique guide provides detailed insights into the nuances of a proven investment strategy. Filled with in-depth insights and expert advice, Statistical Arbitrage contains comprehensive analysis that will appeal to both investors looking for an overview of this discipline, as well as quants looking for critical insights into modeling, risk management, and implementation of the strategy.

Quantitative Trading Book

Quantitative Trading


  • Author : Xin Guo
  • Publisher : CRC Press
  • Release Date : 2017-01-06
  • Genre: Business & Economics
  • Pages : 313
  • ISBN 10 : 9781315354354

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Quantitative Trading Excerpt :

The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part covers market impact models, network models, multi-asset trading, machine learning techniques, and nonlinear filtering. The third part discusses electronic market making, liquidity, systemic risk, recent developments and debates on the subject.

Python for Algorithmic Trading Book

Python for Algorithmic Trading


  • Author : Yves Hilpisch
  • Publisher : O'Reilly Media
  • Release Date : 2020-11-12
  • Genre: Computers
  • Pages : 380
  • ISBN 10 : 9781492053323

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Python for Algorithmic Trading Excerpt :

Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms

Quantitative Trading Book
Score: 4
From 1 Ratings

Quantitative Trading


  • Author : Ernest P. Chan
  • Publisher : Unknown
  • Release Date : 2009
  • Genre: Investment analysis
  • Pages : 181
  • ISBN 10 : 1119203376

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Quantitative Trading Excerpt :

"While institutional traders continue to implement quantitative (or algorithmic) trading, many independent traders have wondered if they can still challenge powerful industry professionals at their own game? The answer is "yes," and in Quantitative Trading, Dr. Ernest Chan, a respected independent trader and consultant, will show you how. Whether you're an independent "retail" trader looking to start your own quantitative trading business or an individual who aspires to work as a quantitative trader at a major financial institution, this practical guide contains the information you need to succeed"--Resource description page.

Financial Trading and Investing Book

Financial Trading and Investing


  • Author : John L. Teall
  • Publisher : Academic Press
  • Release Date : 2018-03-21
  • Genre: Business & Economics
  • Pages : 522
  • ISBN 10 : 9780128111178

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Financial Trading and Investing Excerpt :

Financial Trading and Investing, Second Edition, delivers the most current information on trading and market microstructure for undergraduate and master’s students. Without demanding a background in econometrics, it explores alternative markets and highlights recent regulatory developments, implementations, institutions and debates. New explanations of controversial trading tactics (and blunders), such as high-frequency trading, dark liquidity pools, fat fingers, insider trading, and flash orders emphasize links between the history of financial regulation and events in financial markets. New sections on valuation and hedging techniques, particularly with respect to fixed income and derivatives markets, accompany updated regulatory information. In addition, new case studies and additional exercises are included on a website that has been revised, expanded and updated. Combining theory and application, the book provides the only up-to-date, practical beginner's introduction to today's investment tools and markets. Concentrates on trading, trading institutions, markets and the institutions that facilitate and regulate trading activities Introduces foundational topics relating to trading and securities markets, including auctions, market microstructure, the roles of information and inventories, behavioral finance, market efficiency, risk, arbitrage, trading technology, trading regulation and ECNs Covers market and technology advances and innovations, such as execution algo trading, Designated Market Makers (DMMs), Supplemental Liquidity Providers (SLPs), and the Super Display Book system (SDBK)

Artificial Intelligence in Asset Management Book

Artificial Intelligence in Asset Management


  • Author : Söhnke M. Bartram
  • Publisher : CFA Institute Research Foundation
  • Release Date : 2020-08-28
  • Genre: Business & Economics
  • Pages : 96
  • ISBN 10 : 9781952927034

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Artificial Intelligence in Asset Management Excerpt :

Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

Electronic and Algorithmic Trading Technology Book
Score: 2.5
From 2 Ratings

Electronic and Algorithmic Trading Technology


  • Author : Kendall Kim
  • Publisher : Academic Press
  • Release Date : 2010-07-27
  • Genre: Business & Economics
  • Pages : 224
  • ISBN 10 : 0080548865

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Electronic and Algorithmic Trading Technology Excerpt :

Electronic and algorithmic trading has become part of a mainstream response to buy-side traders’ need to move large blocks of shares with minimum market impact in today’s complex institutional trading environment. This book illustrates an overview of key providers in the marketplace. With electronic trading platforms becoming increasingly sophisticated, more cost effective measures handling larger order flow is becoming a reality. The higher reliance on electronic trading has had profound implications for vendors and users of information and trading products. Broker dealers providing solutions through their products are facing changes in their business models such as: relationships with sellside customers, relationships with buyside customers, the importance of broker neutrality, the role of direct market access, and the relationship with prime brokers. Electronic and Algorithmic Trading Technology: The Complete Guide is the ultimate guide to managers, institutional investors, broker dealers, and software vendors to better understand innovative technologies that can cut transaction costs, eliminate human error, boost trading efficiency and supplement productivity. As economic and regulatory pressures are driving financial institutions to seek efficiency gains by improving the quality of software systems, firms are devoting increasing amounts of financial and human capital to maintaining their competitive edge. This book is written to aid the management and development of IT systems for financial institutions. Although the book focuses on the securities industry, its solution framework can be applied to satisfy complex automation requirements within very different sectors of financial services – from payments and cash management, to insurance and securities. Electronic and Algorithmic Trading: The Complete Guide is geared toward all levels of technology, investment management and the financial service professionals responsible for developing and implementing cu

Building Winning Algorithmic Trading Systems Book
Score: 4
From 1 Ratings

Building Winning Algorithmic Trading Systems


  • Author : Kevin J. Davey
  • Publisher : John Wiley & Sons
  • Release Date : 2014-06-11
  • Genre: Business & Economics
  • Pages : 288
  • ISBN 10 : 9781118778883

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Building Winning Algorithmic Trading Systems Excerpt :

Develop your own trading system with practical guidance and expert advice In Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Training, award-winning trader Kevin Davey shares his secrets for developing trading systems that generate triple-digit returns. With both explanation and demonstration, Davey guides you step-by-step through the entire process of generating and validating an idea, setting entry and exit points, testing systems, and implementing them in live trading. You'll find concrete rules for increasing or decreasing allocation to a system, and rules for when to abandon one. The companion website includes Davey's own Monte Carlo simulator and other tools that will enable you to automate and test your own trading ideas. A purely discretionary approach to trading generally breaks down over the long haul. With market data and statistics easily available, traders are increasingly opting to employ an automated or algorithmic trading system—enough that algorithmic trades now account for the bulk of stock trading volume. Building Algorithmic Trading Systems teaches you how to develop your own systems with an eye toward market fluctuations and the impermanence of even the most effective algorithm. Learn the systems that generated triple-digit returns in the World Cup Trading Championship Develop an algorithmic approach for any trading idea using off-the-shelf software or popular platforms Test your new system using historical and current market data Mine market data for statistical tendencies that may form the basis of a new system Market patterns change, and so do system results. Past performance isn't a guarantee of future success, so the key is to continually develop new systems and adjust established systems in response to evolving statistical tendencies. For individual traders looking for the next leap forward, Building Algorithmic Trading Systems provides expert guidance and practical advice.

Global Algorithmic Capital Markets Book

Global Algorithmic Capital Markets


  • Author : Walter Mattli
  • Publisher : Oxford University Press, USA
  • Release Date : 2019-01-03
  • Genre: Business & Economics
  • Pages : 385
  • ISBN 10 : 9780198829461

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Global Algorithmic Capital Markets Excerpt :

Global capital markets have undergone fundamental transformations in recent years and, as a result, have become extraordinarily complex and opaque. Trading space is no longer measured in minutes or seconds but in time units beyond human perception: milliseconds, microseconds, and even nanoseconds. Technological advances have thus scaled up imperceptible and previously irrelevant time differences into operationally manageable and enormously profitable business opportunities for those with the proper high-tech trading tools. These tools include the fastest private communication and trading lines, the most powerful computers and sophisticated algorithms capable of speedily analysing incoming news and trading data and determining optimal trading strategies in microseconds, as well as the possession of gigantic collections of historic and real-time market data. Fragmented capital markets are also becoming a rapidly growing reality in Europe and Asia, and are an established feature of U.S. trading. This raises urgent market governance issues that have largely been overlooked. Global Algorithmic Capital Markets seeks to understand how recent market transformations are affecting core public policy objectives such as investor protection and reduction of systemic risk, as well as fairness, efficiency, and transparency. The operation and health of capital markets affect all of us and have profound implications for equality and justice in society. This unique set of chapters by leading scholars, industry insiders, and regulators discusses ways to strengthen market governance for the benefit of society at whole.

Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments Book

Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments


  • Author : David Aronson
  • Publisher : Createspace Independent Pub
  • Release Date : 2013
  • Genre: Business & Economics
  • Pages : 520
  • ISBN 10 : 148950771X

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Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments Excerpt :

This book serves two purposes. First, it teaches the importance of using sophisticated yet accessible statistical methods to evaluate a trading system before it is put to real-world use. In order to accommodate readers having limited mathematical background, these techniques are illustrated with step-by-step examples using actual market data, and all examples are explained in plain language. Second, this book shows how the free program TSSB (Trading System Synthesis & Boosting) can be used to develop and test trading systems. The machine learning and statistical algorithms available in TSSB go far beyond those available in other off-the-shelf development software. Intelligent use of these state-of-the-art techniques greatly improves the likelihood of obtaining a trading system whose impressive backtest results continue when the system is put to use in a trading account. Among other things, this book will teach the reader how to: Estimate future performance with rigorous algorithms Evaluate the influence of good luck in backtests Detect overfitting before deploying your system Estimate performance bias due to model fitting and selection of seemingly superior systems Use state-of-the-art ensembles of models to form consensus trade decisions Build optimal portfolios of trading systems and rigorously test their expected performance Search thousands of markets to find subsets that are especially predictable Create trading systems that specialize in specific market regimes such as trending/flat or high/low volatility More information on the TSSB program can be found at TSSBsoftware dot com.

Algorithmic Trading Book

Algorithmic Trading


  • Author : Ernie Chan
  • Publisher : John Wiley & Sons
  • Release Date : 2013-05-28
  • Genre: Business & Economics
  • Pages : 224
  • ISBN 10 : 9781118460146

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Algorithmic Trading Excerpt :

Praise for Algorithmic Trading "Algorithmic Trading is an insightful book on quantitative trading written by a seasoned practitioner. What sets this book apart from many others in the space is the emphasis on real examples as opposed to just theory. Concepts are not only described, they are brought to life with actual trading strategies, which give the reader insight into how and why each strategy was developed, how it was implemented, and even how it was coded. This book is a valuable resource for anyone looking to create their own systematic trading strategies and those involved in manager selection, where the knowledge contained in this book will lead to a more informed and nuanced conversation with managers." —DAREN SMITH, CFA, CAIA, FSA, President and Chief Investment Officer, University of Toronto Asset Management "Using an excellent selection of mean reversion and momentum strategies, Ernie explains the rationale behind each one, shows how to test it, how to improve it, and discusses implementation issues. His book is a careful, detailed exposition of the scientific method applied to strategy development. For serious retail traders, I know of no other book that provides this range of examples and level of detail. His discussions of how regime changes affect strategies, and of risk management, are invaluable bonuses." —Roger Hunter, Mathematician and Algorithmic Trader