Have you ever noticed that most of the best traders are avid readers? Ask any trader for a list of their favorite books and you’ll get an enthusiastic response.

And in fact, one of the most frequent questions we get is…

…what are the best books for algo traders?

In this 2nd episode of the trading book series, we focus on our top 4 favorite trading books for ADVANCED traders.

“Evidence-Based Technical Analysis” – David Aronson

  • A very healthy view on natural human biases
  • A deeper understanding of the danger of survival bias and data-mining biases
  • Pushes your boundaries
  • Makes you seriously think about every step of your development and robustness testing process
  • MY FAVORITE PART: Data mining case study at the end

Get the book on Amazon: https://amzn.to/3wDgnIG 

“The Definitive Guide to Position Sizing Strategies” – Van Tharp

  • The very best book on position sizing out there
  • Gave me the final confidence to launch my own hedge fund
  • Goes really deep but highly practical
  • Will seriously help you improve your results with position-sizing
  • MY FAVORITE PART:  SQN

Get the book on Amazon: https://amzn.to/3WOvOZ8

“Statistically Sound Indicators for Financial Market Prediction” – Timothy Masters

  • A very different view
  • A ton of interesting ideas
  • Makes you questions some parts of your development process (which is a GOOD thing)
  • Not for everyone, a bit more difficult
  • MY FAVORITE PART: Entropy

Get the book on Amazon: https://amzn.to/3WPHef2

“The Psychology of Trading” – Brett Steenbarger

  • A very different view on why many traders do not succeed
  • Seriously helps you to understand some of your trading-related actions and behaviours better
  • Very practical and very precisely focused on traders
  • MY FAVOURITE PART: The Entire Book

Get the book on Amazon: https://amzn.to/3YbNWwX

Take the Trading Book Challenge

Watch the Replay of the Advanced Algo-trading book review

Check out our top 4 list of books for beginner traders

DISCLAIMER: Trading involves significant risk of loss and is not suitable for everyone. People can and do lose money. Hypothetical results have many inherent limitations. Past performance is not necessarily indicative of future results.

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