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MACHINE TRADING DEPLOYING ALGORITHMS TO CONQUER THE MARKETS (HB 2017)
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MACHINE TRADING DEPLOYING ALGORITHMS TO CONQUER THE MARKETS (HB 2017) Hardcover - 2017

by CHAN E P

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Details

  • Title MACHINE TRADING DEPLOYING ALGORITHMS TO CONQUER THE MARKETS (HB 2017)
  • Author CHAN E P
  • Binding Hardcover
  • Edition Hardback
  • Condition New
  • Pages 272
  • Volumes 1
  • Language ENG
  • Publisher Wiley
  • Date 2017-02-06
  • Features Bibliography, Index
  • Bookseller's Inventory # BIBR-47044
  • ISBN 9781119219606 / 1119219604
  • Weight 1 lbs (0.45 kg)
  • Dimensions 9.1 x 6.1 x 1.2 in (23.11 x 15.49 x 3.05 cm)
  • Library of Congress subjects Electronic trading of securities, Computer algorithms
  • Library of Congress Catalog Number 2016039538
  • Dewey Decimal Code 332.640

From the jacket flap

Following up on his widely popular algorithmic trading guides, Quantitative Trading and Algorithmic Trading, this third installment is written for quant traders and investors ready for more advanced examinations and techniques. Machine Trading is your accessible companion for the state-of-the-art of algo-trading in today's complex markets.

Don't worry if you lack trading and finance experience--if you've worked in a quantitative field, such as computer science, engineering, or physics, this step-by-step resource makes the transition into algorithmic trading seamless. It starts out with a comprehensive look at the latest backtesting and trading platforms, the best- rated and most cost-effective vendors' data, and the easiest way to optimize allocations in different assets and strategies. Acquire a firm grasp on options and volatility strategies; factor models, and why they can be useful to short-term traders; and the intricacies of intraday and high-frequency trading, including market microstructure, dark pools, order flow, and backtesting intraday strategies with tick data. There are no canned solutions inside--each prototype trading strategy provides a rock solid foundation for you to customize. Hone your skillset on topics such as:

  • Using factor models for long-term returns and short-term trades, including using option prices as factors
  • Real-world trading with time series techniques, including ARIMA, VAR, and State Space Models with hidden variables
  • Cutting-edge techniques to reduce outfitting in artificial intelligence and machine learning strategies

Every chapter includes hands-on exercises walking you through the critical modifications to make on your own to gain control of the strategies and discover their potential. From stocks to futures and options, foreign exchange, and bitcoins, Machine Trading is your one-stop training ground for finding algo-trading solutions.

About the author

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.