Building Winning Algorithmic Trading SystemsUnlock the secrets to successful trading with *Building Winning Algorithmic Trading Systems*. This comprehensive guide empowers both novice and seasoned traders to develop their own winning trading systems. Based on the expertise of award winning trader Kevin Davey, this book provides practical guidance, enabling you to navigate the intricate world of algorithmic trading. With the *Building Winning Algorithmic Trading Systems*, you'll embark on a
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Unlock the secrets to successful trading with *Building Winning Algorithmic Trading Systems*. This comprehensive guide empowers both novice and seasoned traders to develop their own winning trading systems. Based on the expertise of award-winning trader Kevin Davey, this book provides practical guidance, enabling you to navigate the intricate world of algorithmic trading.
With the *Building Winning Algorithmic Trading Systems*, you'll embark on a journey from data mining to advanced Monte Carlo simulations and live trading strategies. Every essential component is covered, from generating and validating trading ideas to setting precise entry and exit points. Packed with proven techniques for testing systems, this book arms you with the knowledge to maximize your trading potential. Learn to recognize market trends and fluctuations to enhance your algorithm's performance, ensuring it adapts effectively to the dynamic market environment.
The companion website also enriches your learning experience, providing tools such as Davey's custom Monte Carlo simulator, designed to help you automate and rigorously test your trading systems before live deployment. As algorithmic trading continues to dominate stock trading volume, understanding how to create effective and robust systems has never been more vital.
*Learn the tested systems that achieved triple-digit returns in the World Cup Trading Championship!* *Ideal for traders ready to embrace automation and demand precision in trading, this book helps you grasp the art and science of algorithmic trading.*
Condition: BRAND NEW ISBN: 9781118778982 Year: 2014 Publisher: John Wiley & Sons Inc (US) Pages: 288 Note: Shipping for this item is free. Please allow up to 6 weeks for delivery. Once your order is placed, it cannot be cancelled.
Note: Shipping for this item is free. Please allow up to 6 weeks for delivery. Once your order is placed, it cannot be cancelled.
Condition: BRAND NEW ISBN: 9781118778982 Year: 2014 Publisher: John Wiley & Sons Inc (US) Pages: 288
Description: 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 for