The Science of Algorithmic Trading and Portfolio Management

The Science of Algorithmic Trading and Portfolio Management
Author: Robert Kissell
Publsiher: Academic Press
Total Pages: 496
Release: 2013-10-01
ISBN 10: 0124016936
ISBN 13: 9780124016934
Language: EN, FR, DE, ES & NL

The Science of Algorithmic Trading and Portfolio Management Book Review:

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.

The Science of Algorithmic Trading and Portfolio Management

The Science of Algorithmic Trading and Portfolio Management
Author: Robert Kissell
Publsiher: Academic Press
Total Pages: 473
Release: 2013-07-01
ISBN 10: 9780124016897
ISBN 13: 0124016898
Language: EN, FR, DE, ES & NL

The Science of Algorithmic Trading and Portfolio Management Book Review:

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

Algorithmic Trading Methods
Author: Robert L. Kissell
Publsiher: Academic Press
Total Pages: 612
Release: 2020-09-08
ISBN 10: 0128156317
ISBN 13: 9780128156315
Language: EN, FR, DE, ES & NL

Algorithmic Trading Methods Book Review:

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.

A Guide to Creating A Successful Algorithmic Trading Strategy

A Guide to Creating A Successful Algorithmic Trading Strategy
Author: Perry J. Kaufman
Publsiher: John Wiley & Sons
Total Pages: 192
Release: 2016-02-01
ISBN 10: 1119224748
ISBN 13: 9781119224747
Language: EN, FR, DE, ES & NL

A Guide to Creating A Successful Algorithmic Trading Strategy Book Review:

Turn insight into profit with guru guidance toward successful algorithmic trading A Guide to Creating a Successful Algorithmic Trading Strategy provides the latest strategies from an industry guru to show you how to build your own system from the ground up. If you're looking to develop a successful career in algorithmic trading, this book has you covered from idea to execution as you learn to develop a trader's insight and turn it into profitable strategy. You'll discover your trading personality and use it as a jumping-off point to create the ideal algo system that works the way you work, so you can achieve your goals faster. Coverage includes learning to recognize opportunities and identify a sound premise, and detailed discussion on seasonal patterns, interest rate-based trends, volatility, weekly and monthly patterns, the 3-day cycle, and much more—with an emphasis on trading as the best teacher. By actually making trades, you concentrate your attention on the market, absorb the effects on your money, and quickly resolve problems that impact profits. Algorithmic trading began as a "ridiculous" concept in the 1970s, then became an "unfair advantage" as it evolved into the lynchpin of a successful trading strategy. This book gives you the background you need to effectively reap the benefits of this important trading method. Navigate confusing markets Find the right trades and make them Build a successful algo trading system Turn insights into profitable strategies Algorithmic trading strategies are everywhere, but they're not all equally valuable. It's far too easy to fall for something that worked brilliantly in the past, but with little hope of working in the future. A Guide to Creating a Successful Algorithmic Trading Strategy shows you how to choose the best, leave the rest, and make more money from your trades.

Algorithmic Trading and Quantitative Strategies

Algorithmic Trading and Quantitative Strategies
Author: Raja Velu
Publsiher: CRC Press
Total Pages: 400
Release: 2020-08-06
ISBN 10: 1498737218
ISBN 13: 9781498737210
Language: EN, FR, DE, ES & NL

Algorithmic Trading and Quantitative Strategies Book Review:

Algorithmic Trading and Quantitative Strategies provides an in-depth overview of this growing field with a unique mix of quantitative rigor and practitioner’s hands-on experience. The focus on empirical modeling and practical know-how makes this book a valuable resource for students and professionals. The book starts with the often overlooked context of why and how we trade via a detailed introduction to market structure and quantitative microstructure models. The authors then present the necessary quantitative toolbox including more advanced machine learning models needed to successfully operate in the field. They next discuss the subject of quantitative trading, alpha generation, active portfolio management and more recent topics like news and sentiment analytics. The last main topic of execution algorithms is covered in detail with emphasis on the state of the field and critical topics including the elusive concept of market impact. The book concludes with a discussion on the technology infrastructure necessary to implement algorithmic strategies in large-scale production settings. A git-hub repository includes data-sets and explanatory/exercise Jupyter notebooks. The exercises involve adding the correct code to solve the particular analysis/problem.

An Introduction to Algorithmic Trading

An Introduction to Algorithmic Trading
Author: Edward Leshik,Jane Cralle
Publsiher: John Wiley & Sons
Total Pages: 272
Release: 2011-09-19
ISBN 10: 1119975093
ISBN 13: 9781119975090
Language: EN, FR, DE, ES & NL

An Introduction to Algorithmic Trading Book Review:

Interest in algorithmic trading is growing massively – it’s cheaper, faster and better to control than standard trading, it enables you to ‘pre-think’ the market, executing complex math in real time and take the required decisions based on the strategy defined. We are no longer limited by human ‘bandwidth’. The cost alone (estimated at 6 cents per share manual, 1 cent per share algorithmic) is a sufficient driver to power the growth of the industry. According to consultant firm, Aite Group LLC, high frequency trading firms alone account for 73% of all US equity trading volume, despite only representing approximately 2% of the total firms operating in the US markets. Algorithmic trading is becoming the industry lifeblood. But it is a secretive industry with few willing to share the secrets of their success. The book begins with a step-by-step guide to algorithmic trading, demystifying this complex subject and providing readers with a specific and usable algorithmic trading knowledge. It provides background information leading to more advanced work by outlining the current trading algorithms, the basics of their design, what they are, how they work, how they are used, their strengths, their weaknesses, where we are now and where we are going. The book then goes on to demonstrate a selection of detailed algorithms including their implementation in the markets. Using actual algorithms that have been used in live trading readers have access to real time trading functionality and can use the never before seen algorithms to trade their own accounts. The markets are complex adaptive systems exhibiting unpredictable behaviour. As the markets evolve algorithmic designers need to be constantly aware of any changes that may impact their work, so for the more adventurous reader there is also a section on how to design trading algorithms. All examples and algorithms are demonstrated in Excel on the accompanying CD ROM, including actual algorithmic examples which have been used in live trading.

Algorithmic Trading

Algorithmic Trading
Author: Ernie Chan
Publsiher: John Wiley & Sons
Total Pages: 224
Release: 2013-05-28
ISBN 10: 1118460146
ISBN 13: 9781118460146
Language: EN, FR, DE, ES & NL

Algorithmic Trading Book Review:

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

Statistical Arbitrage

Statistical Arbitrage
Author: Andrew Pole
Publsiher: John Wiley & Sons
Total Pages: 230
Release: 2011-07-07
ISBN 10: 1118160738
ISBN 13: 9781118160732
Language: EN, FR, DE, ES & NL

Statistical Arbitrage Book Review:

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.

Building Winning Algorithmic Trading Systems

Building Winning Algorithmic Trading Systems
Author: Kevin J. Davey
Publsiher: John Wiley & Sons
Total Pages: 288
Release: 2014-06-11
ISBN 10: 111877888X
ISBN 13: 9781118778883
Language: EN, FR, DE, ES & NL

Building Winning Algorithmic Trading Systems Book Review:

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.

Hands On Machine Learning for Algorithmic Trading

Hands On Machine Learning for Algorithmic Trading
Author: Stefan Jansen
Publsiher: Packt Publishing Ltd
Total Pages: 684
Release: 2018-12-31
ISBN 10: 1789342716
ISBN 13: 9781789342710
Language: EN, FR, DE, ES & NL

Hands On Machine Learning for Algorithmic Trading Book Review:

With the help of this book, you'll build smart algorithmic models using machine learning algorithms covering tasks such as time series forecasting, backtesting, trade predictions, and more using easy-to-follow examples. By the end, you'll be able to adopt algorithmic trading in your own business and implement intelligent investigative strategies.

Algorithmic Trading with Python

Algorithmic Trading with Python
Author: Chris Conlan
Publsiher: Independently Published
Total Pages: 126
Release: 2020-04-09
ISBN 10: 1928374650XXX
ISBN 13: 9798632784986
Language: EN, FR, DE, ES & NL

Algorithmic Trading with Python Book Review:

Algorithmic Trading with Python discusses modern quant trading methods in Python with a heavy focus on pandas, numpy, and scikit-learn. After establishing an understanding of technical indicators and performance metrics, readers will walk through the process of developing a trading simulator, strategy optimizer, and financial machine learning pipeline. This book maintains a high standard of reprocibility. All code and data is self-contained in a GitHub repo. The data includes hyper-realistic simulated price data and alternative data based on real securities. Algorithmic Trading with Python (2020) is the spiritual successor to Automated Trading with R (2016). This book covers more content in less time than its predecessor due to advances in open-source technologies for quantitative analysis.

An Introduction to Algorithmic Trading

An Introduction to Algorithmic Trading
Author: Edward Leshik,Jane Cralle
Publsiher: John Wiley & Sons
Total Pages: 272
Release: 2011-04-04
ISBN 10: 0470689544
ISBN 13: 9780470689547
Language: EN, FR, DE, ES & NL

An Introduction to Algorithmic Trading Book Review:

CD-ROM includes examples and algorithms in Microsoft Excel spreadsheets.

Quantitative Trading

Quantitative Trading
Author: Ernest P. Chan
Publsiher: Unknown
Total Pages: 181
Release: 2009
ISBN 10: 9781119203377
ISBN 13: 1119203376
Language: EN, FR, DE, ES & NL

Quantitative Trading Book Review:

"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.

Learn Algorithmic Trading

Learn Algorithmic Trading
Author: Sourav Ghosh,Sebastien Donadio
Publsiher: Unknown
Total Pages: 394
Release: 2019-11-07
ISBN 10: 9781789348347
ISBN 13: 178934834X
Language: EN, FR, DE, ES & NL

Learn Algorithmic Trading Book Review:

Understand the fundamentals of algorithmic trading to apply algorithms to real market data and analyze the results of real-world trading strategies Key Features Understand the power of algorithmic trading in financial markets with real-world examples Get up and running with the algorithms used to carry out algorithmic trading Learn to build your own algorithmic trading robots which require no human intervention Book Description It's now harder than ever to get a significant edge over competitors in terms of speed and efficiency when it comes to algorithmic trading. Relying on sophisticated trading signals, predictive models and strategies can make all the difference. This book will guide you through these aspects, giving you insights into how modern electronic trading markets and participants operate. You'll start with an introduction to algorithmic trading, along with setting up the environment required to perform the tasks in the book. You'll explore the key components of an algorithmic trading business and aspects you'll need to take into account before starting an automated trading project. Next, you'll focus on designing, building and operating the components required for developing a practical and profitable algorithmic trading business. Later, you'll learn how quantitative trading signals and strategies are developed, and also implement and analyze sophisticated trading strategies such as volatility strategies, economic release strategies, and statistical arbitrage. Finally, you'll create a trading bot from scratch using the algorithms built in the previous sections. By the end of this book, you'll be well-versed with electronic trading markets and have learned to implement, evaluate and safely operate algorithmic trading strategies in live markets. What you will learn Understand the components of modern algorithmic trading systems and strategies Apply machine learning in algorithmic trading signals and strategies using Python Build, visualize and analyze trading strategies based on mean reversion, trend, economic releases and more Quantify and build a risk management system for Python trading strategies Build a backtester to run simulated trading strategies for improving the performance of your trading bot Deploy and incorporate trading strategies in the live market to maintain and improve profitability Who this book is for This book is for software engineers, financial traders, data analysts, and entrepreneurs. Anyone who wants to get started with algorithmic trading and understand how it works; and learn the components of a trading system, protocols and algorithms required for black box and gray box trading, and techniques for building a completely automated and profitable trading business will also find this book useful.

Algorithmic and High Frequency Trading

Algorithmic and High Frequency Trading
Author: Álvaro Cartea,Sebastian Jaimungal,José Penalva
Publsiher: Cambridge University Press
Total Pages: 356
Release: 2015-08-06
ISBN 10: 1107091144
ISBN 13: 9781107091146
Language: EN, FR, DE, ES & NL

Algorithmic and High Frequency Trading Book Review:

A straightforward guide to the mathematics of algorithmic trading that reflects cutting-edge research.

Machine Learning for Algorithmic Trading Second Edition

Machine Learning for Algorithmic Trading   Second Edition
Author: Stefan Jansen
Publsiher: Unknown
Total Pages: 820
Release: 2020-07-31
ISBN 10: 9781839217715
ISBN 13: 1839217715
Language: EN, FR, DE, ES & NL

Machine Learning for Algorithmic Trading Second Edition Book Review:

Algorithmic Trading

Algorithmic Trading
Author: Sophia Foster
Publsiher: Unknown
Total Pages: 264
Release: 2021-05-24
ISBN 10: 9781801567640
ISBN 13: 1801567646
Language: EN, FR, DE, ES & NL

Algorithmic Trading Book Review:

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.

Python for Algorithmic Trading

Python for Algorithmic Trading
Author: Yves Hilpisch
Publsiher: O'Reilly Media
Total Pages: 380
Release: 2020-11-12
ISBN 10: 1492053325
ISBN 13: 9781492053323
Language: EN, FR, DE, ES & NL

Python for Algorithmic Trading Book Review:

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

Algorithmic Trading

Algorithmic Trading
Author: Jeffrey Bacidore
Publsiher: Unknown
Total Pages: 135
Release: 2021-02-16
ISBN 10: 9780578862620
ISBN 13: 057886262X
Language: EN, FR, DE, ES & NL

Algorithmic Trading Book Review:

The book provides detailed coverage of?Single order algorithms, such as Volume-Weighted Average Price (VWAP), Time-Weighted-Average Price (TWAP), Percent of Volume (POV), and variants of the Implementation Shortfall algorithm. ?Multi-order algorithms, such as Pairs Trading and Portfolio Trading algorithms.?Smart routers, including "smart market", "smart limit", and dark aggregators.?Trading performance measurement, including trading benchmarks, "algo wheels", trading cost models, and other measurement issues.

High Frequency Trading

High Frequency Trading
Author: Irene Aldridge
Publsiher: John Wiley and Sons
Total Pages: 368
Release: 2009-12-22
ISBN 10: 9780470579770
ISBN 13: 0470579773
Language: EN, FR, DE, ES & NL

High Frequency Trading Book Review:

A hands-on guide to the fast and ever-changing world of high-frequency, algorithmic trading Financial markets are undergoing rapid innovation due to the continuing proliferation of computer power and algorithms. These developments have created a new investment discipline called high-frequency trading. This book covers all aspects of high-frequency trading, from the business case and formulation of ideas through the development of trading systems to application of capital and subsequent performance evaluation. It also includes numerous quantitative trading strategies, with market microstructure, event arbitrage, and deviations arbitrage discussed in great detail. Contains the tools and techniques needed for building a high-frequency trading system Details the post-trade analysis process, including key performance benchmarks and trade quality evaluation Written by well-known industry professional Irene Aldridge Interest in high-frequency trading has exploded over the past year. This book has what you need to gain a better understanding of how it works and what it takes to apply this approach to your trading endeavors.