Machine Trading: Deploying Computer Algorithms to Conquer the Markets

ISBN-13: 9781119219606 / Angielski / Twarda / 2017 / 272 str.

Ernest P. (Cornell University) Chan

Opis

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.

Spis treści

Preface ix

CHAPTER 1 The Basics of Algorithmic Trading 1

CHAPTER 2 Factor Models 27

CHAPTER 3 Time–Series Analysis 59

CHAPTER 4 Artificial Intelligence Techniques 83

CHAPTER 5 Options Strategies 119

CHAPTER 6 Intraday Trading and Market Microstructure 159

CHAPTER 7 Bitcoins 201

CHAPTER 8 Algorithmic Trading Is Good for Body and Soul 215

Bibliography 227

About the Author 235

Index 237

O autorze

ERNEST P. CHAN is the managing member of QTS Capital Management, LLC, a commodity pool operator and trading advisor since 2011. An alumnus of Morgan Stanley and Credit Suisse, he received his PhD in physics from Cornell University, and was a researcher in machine learning at IBM′s T. J. Watson Research Center before joining the financial industry. He is the author of Quantitative Trading and Algorithmic Trading. Find out more about Ernie at www.epchan.com.

Blurb

Praise for Machine Trading

"It is easy to make simple ideas complex. It is far more difficult to make complex ideas seem simple. In this book, Ernie has done exactly that. I cannot think of any trader who would not benefit from reading Machine Trading."
Euan Sinclair, Partner, Talton Capital Management; author, Volatility Trading

"As with his first two books, Ernie delves into the practical matters of automated trading in Machine Trading. He carefully explains everything from where to find quality data, to which platforms to consider, to timely and topical strategies. In the years since his last book, automation of the investment industry has accelerated, due in large part to the recent Cambrian Explosion in financial technology (FinTech). Ernie has long been teaching the hard–to–find methods of automated trading; now he is also a guide to the dizzying array of new companies, technologies, and services for automated trading. Machine Trading takes you deeper into the field with new concepts, while still delivering Ernie′s signature explanation of the concrete steps of pursuing your own passion for automated trading."
John Fawcett, CEO and Founder, Quantopian

"Dr. Chan has written another accessible and information–packed book for the quant–minded trader. The book starts with a clear discussion of factor models, advanced time series analysis, and Kalman filters, all of which lead into a detailed description of machine learning and artificial intelligence techniques applied to volatility trading, market microstructure, and even Bitcoins. His focus on finance in a MATLAB context is refreshing and opens the algorithmic trading domain to a whole generation of engineers and quantitative practitioners not familiar with finance but involved in numerate fields like self–driving cars and proteomics. I highly recommend it."
Dr. Taha Jaffer, President, OXOBOXO Inc.; formerly Principal at The Carlyle Group