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

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.

Building Algorithmic Trading Systems Website

Building Algorithmic Trading Systems    Website
Author: Kevin Davey
Publsiher: John Wiley & Sons
Total Pages: 288
Release: 2014-07-21
ISBN 10: 1118778987
ISBN 13: 9781118778982
Language: EN, FR, DE, ES & NL

Building Algorithmic Trading Systems Website 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.

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.

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 Methods

Algorithmic Trading Methods
Author: Robert 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.

The Ultimate Algorithmic Trading System Toolbox Website

The Ultimate Algorithmic Trading System Toolbox   Website
Author: George Pruitt
Publsiher: John Wiley & Sons
Total Pages: 368
Release: 2016-06-20
ISBN 10: 111909657X
ISBN 13: 9781119096573
Language: EN, FR, DE, ES & NL

The Ultimate Algorithmic Trading System Toolbox Website Book Review:

The accessible, beneficial guide to developing algorithmic trading solutions The Ultimate Algorithmic Trading System Toolbox is the complete package savvy investors have been looking for. An integration of explanation and tutorial, this guide takes you from utter novice to out-the-door trading solution as you learn the tools and techniques of the trade. You'll explore the broad spectrum of today's technological offerings, and use several to develop trading ideas using the provided source code and the author's own library, and get practical advice on popular software packages including TradeStation, TradersStudio, MultiCharts, Excel, and more. You'll stop making repetitive mistakes as you learn to recognize which paths you should not go down, and you'll discover that you don't need to be a programmer to take advantage of the latest technology. The companion website provides up-to-date TradeStation code, Excel spreadsheets, and instructional video, and gives you access to the author himself to help you interpret and implement the included algorithms. Algorithmic system trading isn't really all that new, but the technology that lets you program, evaluate, and implement trading ideas is rapidly evolving. This book helps you take advantage of these new capabilities to develop the trading solution you've been looking for. Exploit trading technology without a computer science degree Evaluate different trading systems' strengths and weaknesses Stop making the same trading mistakes over and over again Develop a complete trading solution using provided source code and libraries New technology has enabled the average trader to easily implement their ideas at very low cost, breathing new life into systems that were once not viable. If you're ready to take advantage of the new trading environment but don't know where to start, The Ultimate Algorithmic Trading System Toolbox will help you get on board quickly and easily.

Python for Algorithmic Trading

Python for Algorithmic Trading
Author: Yves Hilpisch
Publsiher: Unknown
Total Pages: 350
Release: 2021-02-09
ISBN 10: 9781492053354
ISBN 13: 149205335X
Language: EN, FR, DE, ES & NL

Python for Algorithmic Trading Book Review:

The financial industry is adopting Python at an increasing rate. Top hedge funds use the language on a daily basis for quantitative research, data exploration, and analysis and for prototyping, testing, and executing trading strategies. There's also a rise in trading activity by individuals and small groups of traders, including many from the technology world. This book is ideal for Python developers, tech-savvy discretionary traders, data analysts, and people who want to become Algo trading professionals or trade their own funds. Author Yves Hilpisch focuses on the practical application of programming to trading rather than theoretical computer science. If you're looking for a guide to help you perform algorithmic, fully-automated trading, this book is for you.

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 Trading

Algorithmic Trading
Author: Jeffrey Bacidore
Publsiher: Unknown
Total Pages: 329
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.

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.

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.

Quantitative Trading

Quantitative Trading
Author: Ernie Chan
Publsiher: Wiley
Total Pages: 208
Release: 2008-11-17
ISBN 10: 9780470284889
ISBN 13: 0470284889
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.

Python Algorithmic Trading Cookbook

Python Algorithmic Trading Cookbook
Author: Pushpak Dagade
Publsiher: Packt Publishing Ltd
Total Pages: 542
Release: 2020-08-28
ISBN 10: 1838982515
ISBN 13: 9781838982515
Language: EN, FR, DE, ES & NL

Python Algorithmic Trading Cookbook Book Review:

Ever wondered what it takes to be an algorithmic trading professional? Look no further, this recipe-based guide will help you uncover various common and not-so-common challenges faced while devising efficient and powerful algo trading strategies. You will implement various Python libraries to conduct key tasks in the algorithmic trading ecosystem.

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:

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.

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.

Algorithmic Trading with Interactive Brokers

Algorithmic Trading with Interactive Brokers
Author: Matthew Scarpino
Publsiher: Unknown
Total Pages: 329
Release: 2019-09-03
ISBN 10: 9780997303735
ISBN 13: 0997303735
Language: EN, FR, DE, ES & NL

Algorithmic Trading with Interactive Brokers Book Review:

Through Interactive Brokers, software developers can write applications that read financial data, scan for contracts, and submit orders automatically. Individuals can now take advantage of the same high-speed decision making and order placement that professional trading firms use.This book walks through the process of developing applications based on IB's Trader Workstation (TWS) programming interface. Beginning chapters introduce the fundamental classes and functions, while later chapters show how they can be used to implement full-scale trading systems. With an algorithmic system in place, traders don't have to stare at charts for hours on end. Just launch the trading application and let the TWS API do its work.The material in this book focuses on Python and C++ coding, so readers are presumed to have a basic familiarity with one of these languages. However, no experience in financial trading is assumed. If you're new to the world of stocks, bonds, options, and futures, this book explains what these financial instruments are and how to write applications capable of trading them.

Electronic and Algorithmic Trading Technology

Electronic and Algorithmic Trading Technology
Author: Kendall Kim
Publsiher: Academic Press
Total Pages: 224
Release: 2010-07-27
ISBN 10: 9780080548869
ISBN 13: 0080548865
Language: EN, FR, DE, ES & NL

Electronic and Algorithmic Trading Technology Book Review:

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 cutting-edge technology. It outlines a complete framework for successfully building a software system that provides the functionalities required by the business model. It is revolutionary as the first guide to cover everything from the technologies to how to evaluate tools to best practices for IT management. First book to address the hot topic of how systems can be designed to maximize the benefits of program and algorithmic trading Outlines a complete framework for developing a software system that meets the needs of the firm's business model Provides a robust system for making the build vs. buy decision based on business requirements

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:

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features Implement machine learning algorithms to build, train, and validate algorithmic models Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML workflow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn Implement machine learning techniques to solve investment and trading problems Leverage market, fundamental, and alternative data to research alpha factors Design and fine-tune supervised, unsupervised, and reinforcement learning models Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn Integrate machine learning models into a live trading strategy on Quantopian Evaluate strategies using reliable backtesting methodologies for time series Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.