Search Results: machine-trading

Machine Trading

Deploying Computer Algorithms to Conquer the Markets

Author: Ernest P. Chan

Publisher: John Wiley & Sons

ISBN: 1119219604

Category: Business & Economics

Page: 264

View: 3754

Dive into algo trading with step-by-step tutorials and expert insight Machine Trading is a practical guide to building your algorithmic trading business. Written by a recognized trader with major institution expertise, this book provides step-by-step instruction on quantitative trading and the latest technologies available even outside the Wall Street sphere. You'll discover the latest platforms that are becoming increasingly easy to use, gain access to new markets, and learn new quantitative strategies that are applicable to stocks, options, futures, currencies, and even bitcoins. The companion website provides downloadable software codes, and you'll learn to design your own proprietary tools using MATLAB. The author's experiences provide deep insight into both the business and human side of systematic trading and money management, and his evolution from proprietary trader to fund manager contains valuable lessons for investors at any level. Algorithmic trading is booming, and the theories, tools, technologies, and the markets themselves are evolving at a rapid pace. This book gets you up to speed, and walks you through the process of developing your own proprietary trading operation using the latest tools. Utilize the newer, easier algorithmic trading platforms Access markets previously unavailable to systematic traders Adopt new strategies for a variety of instruments Gain expert perspective into the human side of trading The strength of algorithmic trading is its versatility. It can be used in any strategy, including market-making, inter-market spreading, arbitrage, or pure speculation; decision-making and implementation can be augmented at any stage, or may operate completely automatically. Traders looking to step up their strategy need look no further than Machine Trading for clear instruction and expert solutions.

Machine Trading

Deploying Computer Algorithms to Conquer the Markets

Author: Ernest P. Chan

Publisher: John Wiley & Sons

ISBN: 1119219655

Category: Business & Economics

Page: 264

View: 8624

Dive into algo trading with step-by-step tutorials and expert insight Machine Trading is a practical guide to building your algorithmic trading business. Written by a recognized trader with major institution expertise, this book provides step-by-step instruction on quantitative trading and the latest technologies available even outside the Wall Street sphere. You'll discover the latest platforms that are becoming increasingly easy to use, gain access to new markets, and learn new quantitative strategies that are applicable to stocks, options, futures, currencies, and even bitcoins. The companion website provides downloadable software codes, and you'll learn to design your own proprietary tools using MATLAB. The author's experiences provide deep insight into both the business and human side of systematic trading and money management, and his evolution from proprietary trader to fund manager contains valuable lessons for investors at any level. Algorithmic trading is booming, and the theories, tools, technologies, and the markets themselves are evolving at a rapid pace. This book gets you up to speed, and walks you through the process of developing your own proprietary trading operation using the latest tools. Utilize the newer, easier algorithmic trading platforms Access markets previously unavailable to systematic traders Adopt new strategies for a variety of instruments Gain expert perspective into the human side of trading The strength of algorithmic trading is its versatility. It can be used in any strategy, including market-making, inter-market spreading, arbitrage, or pure speculation; decision-making and implementation can be augmented at any stage, or may operate completely automatically. Traders looking to step up their strategy need look no further than Machine Trading for clear instruction and expert solutions.

Machine Trading

Deploying Computer Algorithms to Conquer the Markets

Author: Ernest P. Chan

Publisher: John Wiley & Sons

ISBN: 1119219671

Category: Business & Economics

Page: 264

View: 5184

Dive into algo trading with step-by-step tutorials and expert insight Machine Trading is a practical guide to building your algorithmic trading business. Written by a recognized trader with major institution expertise, this book provides step-by-step instruction on quantitative trading and the latest technologies available even outside the Wall Street sphere. You'll discover the latest platforms that are becoming increasingly easy to use, gain access to new markets, and learn new quantitative strategies that are applicable to stocks, options, futures, currencies, and even bitcoins. The companion website provides downloadable software codes, and you'll learn to design your own proprietary tools using MATLAB. The author's experiences provide deep insight into both the business and human side of systematic trading and money management, and his evolution from proprietary trader to fund manager contains valuable lessons for investors at any level. Algorithmic trading is booming, and the theories, tools, technologies, and the markets themselves are evolving at a rapid pace. This book gets you up to speed, and walks you through the process of developing your own proprietary trading operation using the latest tools. Utilize the newer, easier algorithmic trading platforms Access markets previously unavailable to systematic traders Adopt new strategies for a variety of instruments Gain expert perspective into the human side of trading The strength of algorithmic trading is its versatility. It can be used in any strategy, including market-making, inter-market spreading, arbitrage, or pure speculation; decision-making and implementation can be augmented at any stage, or may operate completely automatically. Traders looking to step up their strategy need look no further than Machine Trading for clear instruction and expert solutions.

Dark Pools

The Rise of the Machine Traders and the Rigging of the U.S. Stock Market

Author: Scott Patterson

Publisher: Crown Pub

ISBN: 0307887189

Category: Business & Economics

Page: 362

View: 4943

A Wall Street Journal reporter evaluates the cost and consequences of high-speed trading, arguing that the development of automatic, super-intelligent trading machines is eliminating necessary human interests and compromising regulation measures. 50,000 first printing.

Quantitative Trading

How to Build Your Own Algorithmic Trading Business

Author: Ernest P. Chan

Publisher: N.A

ISBN: 9781119203377

Category: Investment analysis

Page: 181

View: 5911

"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.

Algorithmic Trading

Winning Strategies and Their Rationale

Author: Ernie Chan

Publisher: John Wiley & Sons

ISBN: 1118460146

Category: Business & Economics

Page: 207

View: 4477

Markets are now almost always electronic, and as a result of decimalization, algorithmic trading is booming. Algorithmic trading (or "algo trading" as it is referred) is the use of computer programs (such as Excel or MatLab) for entering and executing trading orders with the computer algorithm deciding on certain aspects of the order, such as the timing, price, or even the final quantity of the order. Algorithmic trading may be used in any investment strategy, including market-making, inter-market spreading, arbitrage, or pure speculation (including trend following). The investment decision and implementation may be augmented at any stage with algorithmic support or may operate completely automatically. Algorithmic Trading provides an understanding of the core concepts in quantitative trading, an understanding of the process of using mathematics and statistics to analyze the profitability of a trading model, a “hands on” experience of how backtesting is done, and an understanding of pair trading in stocks, ETFs, futures and currencies. Chan shows investors how to use Excel and MatLab to build their own algo trading tools, as well as FX1, an FX trading platform growing in popularity.He also shows investors how to conduct quantitative research and analysis, and turn quantitative trading strategies into profits using stocks, ETFs, futures, and other financial instruments.

Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments

Developing Predictive-model-based Trading Systems Using TSSB

Author: David Aronson,Timothy Masters

Publisher: Createspace Independent Pub

ISBN: 9781489507716

Category: Business & Economics

Page: 520

View: 5952

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.

Intelligent Trading Systems

Applying Artificial Intelligence to Financial Markets

Author: Ondrej Martinsky

Publisher: Harriman House Limited

ISBN: 1906659532

Category: Business & Economics

Page: 200

View: 2143

This work deals with the issue of problematic market price prediction in the context of crowd behavior. "Intelligent Trading Systems" describes technical analysis methods used to predict price movements.

Betfair Trading Techniques

Trading Models, Machine Learning, Money Management, Monte Carlo Methods & Algorithmic Trading

Author: James Butler

Publisher: Createspace Independent Publishing Platform

ISBN: 9781514286623

Category:

Page: 200

View: 9457

Betting exchanges are becoming ever more like financial markets. This has seen the rise of technical traders who find new and inventive ways of trading, little of it having anything to do with the underlying sports. Manual traders are having to give way to automation and algorithmic trading. To stay ahead, the most successful traders are resorting to systematic and automated methods to build and trade their strategies. This book demonstrates techniques for sports trading, including; fundamental and technical trading, statistical arbitrage, money management, Monte Carlo methods, machine learning and the increasing necessity for algorithmic trading.

Cybernetic Trading Strategies

Developing a Profitable Trading System with State-of-the-Art Technologies

Author: Murray A. Ruggiero

Publisher: John Wiley & Sons

ISBN: 9780471149200

Category: Business & Economics

Page: 315

View: 5417

"The computer can do more than show us pretty pictures. [It] can optimize, backtest, prove or disprove old theories, eliminate the bad ones and make the good ones better. Cybernetic Trading Strategies explores new ways to use the computer and finds ways to make a valuable machine even more valuable." ––from the Foreword by John J. Murphy. Until recently, the computer has been used almost exclusively as a charting and data–gathering tool. But as traders and analysts have quickly discovered, its capabilities are far more vast. Now, in this groundbreaking new book, Murray Ruggiero, a leading authority on cybernetic trading systems, unlocks their incredible potential and provides an in–depth look at the growing impact of advanced technologies on intermarket analysis. A unique resource, Cybernetic Trading Strategies provides specific instructions and applications on how to develop tradable market timing systems using neural networks, fuzzy logic, genetic algorithms, chaos theory, and machine induction methods. Currently utilized by some of the most powerful financial institutions in the world––including John Deere and Fidelity Investments––today′s advanced technologies go beyond subjective interpretations of market indicators to enhance traditional analysis. As a result, existing trading systems gain a competitive edge. Ruggiero reveals how "incorporating elements of statistical analysis, spectral analysis, neural networks, genetic algorithms, fuzzy logic, and other high–tech concepts into a traditional technical trading system can greatly improve the performance of standard trading systems." For example: spectral analysis can be used to detect when a market is trending earlier than classical indicators such as ADX. Drawing on his extensive research on market analysis, Ruggiero provides an incisive overview of cyber–systems––systems that, when applied correctly, can increase trading returns by as much as 200% to 300%. The author covers a wide range of important topics, examining classical technical analysis methodologies and seasonal trading, as well as statistically based market prediction and the mechanization of subjective methods such as candlestick charts and the Elliott Wave. Precise explanations and dozens of real–world examples show you how to: ∗ Incorporate advanced technologies into classical technical analysis methodologies. ∗ Identify which of these technologies have the most market applicability. ∗ Build trading systems to maximize reliability and profitability based on your own risk/reward criteria. Most importantly, Cybernetic Trading Strategies takes you step by step through system testing and evaluation, a crucial step for controlling risk and managing money. With up–to–date information from one of the field′s leading authorities, Cybernetic Trading Strategies is the definitive guide to developing, implementing, and testing today′s cutting–edge computer trading technologies.

Advances in Financial Machine Learning

Author: Marcos Lopez de Prado

Publisher: John Wiley & Sons

ISBN: 1119482119

Category: Business & Economics

Page: 400

View: 6868

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Pairs Trading

Quantitative Methods and Analysis

Author: Ganapathy Vidyamurthy

Publisher: John Wiley & Sons

ISBN: 9781118045701

Category: Business & Economics

Page: 224

View: 9010

The first in-depth analysis of pairs trading Pairs trading is a market-neutral strategy in its most simple form. The strategy involves being long (or bullish) one asset and short (or bearish) another. If properly performed, the investor will gain if the market rises or falls. Pairs Trading reveals the secrets of this rigorous quantitative analysis program to provide individuals and investment houses with the tools they need to successfully implement and profit from this proven trading methodology. Pairs Trading contains specific and tested formulas for identifying and investing in pairs, and answers important questions such as what ratio should be used to construct the pairs properly. Ganapathy Vidyamurthy (Stamford, CT) is currently a quantitative software analyst and developer at a major New York City hedge fund.

Automated Trading with R

Quantitative Research and Platform Development

Author: Chris Conlan

Publisher: Apress

ISBN: 1484221788

Category: Computers

Page: 205

View: 7386

Learn to trade algorithmically with your existing brokerage, from data management, to strategy optimization, to order execution, using free and publicly available data. Connect to your brokerage’s API, and the source code is plug-and-play. Automated Trading with R explains automated trading, starting with its mathematics and moving to its computation and execution. You will gain a unique insight into the mechanics and computational considerations taken in building a back-tester, strategy optimizer, and fully functional trading platform. The platform built in this book can serve as a complete replacement for commercially available platforms used by retail traders and small funds. Software components are strictly decoupled and easily scalable, providing opportunity to substitute any data source, trading algorithm, or brokerage. This book will: Provide a flexible alternative to common strategy automation frameworks, like Tradestation, Metatrader, and CQG, to small funds and retail traders Offer an understanding of the internal mechanisms of an automated trading system Standardize discussion and notation of real-world strategy optimization problems What You Will Learn Understand machine-learning criteria for statistical validity in the context of time-series Optimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package library Best simulate strategy performance in its specific use case to derive accurate performance estimates Understand critical real-world variables pertaining to portfolio management and performance assessment, including latency, drawdowns, varying trade size, portfolio growth, and penalization of unused capital Who This Book Is For Traders/practitioners at the retail or small fund level with at least an undergraduate background in finance or computer science; graduate level finance or data science students

The Science of Algorithmic Trading and Portfolio Management

Author: Robert Kissell

Publisher: Academic Press

ISBN: 0124016936

Category: Business & Economics

Page: 496

View: 1530

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.

Quantitative Trading

Algorithms, Analytics, Data, Models, Optimization

Author: Xin Guo,Tze Leung Lai,Howard Shek,Samuel Po-Shing Wong

Publisher: CRC Press

ISBN: 1315354357

Category: Business & Economics

Page: 379

View: 6688

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.

Building Trading Bots Using Java

Author: Shekhar Varshney

Publisher: Apress

ISBN: 1484225201

Category: Computers

Page: 281

View: 6786

Build an automated currency trading bot from scratch with java. In this book, you will learn about the nitty-gritty of automated trading and have a closer look at Java, the Spring Framework, event-driven programming, and other open source APIs, notably Google's Guava API. And of course, development will all be test-driven with unit testing coverage. The central theme of Building Trading Bots Using Java is to create a framework that can facilitate automated trading on most of the brokerage platforms, with minimum changes. At the end of the journey, you will have a working trading bot, with a sample implementation using the OANDA REST API, which is free to use. What You'll Learn Find out about trading bots Discover the details of tradeable instruments and apply bots to them Track and use market data events Place orders and trades Work with trade/order and account events Who This Book Is For Experienced programmers new to bots and other algorithmic trading and finance techniques.

Advances in Financial Machine Learning

Author: Marcos Lopez de Prado

Publisher: John Wiley & Sons

ISBN: 1119482119

Category: Business & Economics

Page: 400

View: 6503

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Algorithmic and High-Frequency Trading

Author: Álvaro Cartea,Sebastian Jaimungal,José Penalva

Publisher: Cambridge University Press

ISBN: 1316453650

Category: Mathematics

Page: N.A

View: 3222

The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you.

Prediction Machines

The Simple Economics of Artificial Intelligence

Author: Ajay Agrawal,Joshua Gans,Avi Goldfarb

Publisher: Harvard Business Press

ISBN: 1633695689

Category: Computers

Page: 272

View: 8458

"What does AI mean for your business? Read this book to find out." -- Hal Varian, Chief Economist, Google Artificial intelligence does the seemingly impossible, magically bringing machines to life--driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future. But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs. When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity--operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

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