Machine Trading

Machine Trading
Author :
Publisher : John Wiley & Sons
Total Pages : 277
Release :
ISBN-10 : 9781119219606
ISBN-13 : 1119219604
Rating : 4/5 (604 Downloads)

Book Synopsis Machine Trading by : Ernest P. Chan

Download or read book Machine Trading written by Ernest P. Chan and published by John Wiley & Sons. This book was released on 2017-02-06 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Related Books

Machine Trading
Language: en
Pages: 277
Authors: Ernest P. Chan
Categories: Business & Economics
Type: BOOK - Published: 2017-02-06 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Dive into algo trading with step-by-step tutorials and expert insight Machine Trading is a practical guide to building your algorithmic trading business. Writte
Machine Learning for Algorithmic Trading
Language: en
Pages: 822
Authors: Stefan Jansen
Categories: Business & Economics
Type: BOOK - Published: 2020-07-31 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensi
The Science of Algorithmic Trading and Portfolio Management
Language: en
Pages: 496
Authors: Robert Kissell
Categories: Business & Economics
Type: BOOK - Published: 2013-10-01 - Publisher: Academic Press

DOWNLOAD EBOOK

The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from othe
Algorithmic Trading
Language: en
Pages: 230
Authors: Ernie Chan
Categories: Business & Economics
Type: BOOK - Published: 2013-05-28 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Praise for Algorithmic TRADING “Algorithmic Trading is an insightful book on quantitative trading written by a seasoned practitioner. What sets this book apar
Hands-On Machine Learning for Algorithmic Trading
Language: en
Pages: 668
Authors: Stefan Jansen
Categories: Computers
Type: BOOK - Published: 2018-12-31 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key FeaturesImplement machine learning algorithms