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algorithmic-trading's Introduction

Algorithmic Trading

Researching about Algorithmic Trading

I. Books

  • Ref: Recommended Books by neurotrader youtuber
  • Categories: Introduction (beginner), Risk Management, Indicators, Strategies, Trading System Development, Essential Skills for Trading, Niche, Quant Trading.

1. Introduction

  • Systematic Trading by Robert Carver (beginner)
  • Trading Systems and Methods by Perry J.Kaufman (intermediate)
  • Advances in Financial Machine Learning by Marcos Lopez De Prado (advanced)

2. Risk Management

  • The Leverage Space Trading Model by Ralph Vince (intermediate)
  • The Mathematics of Money Management by Ralph Vince (intermediate)

3. Indicators

  • Rocket Science for Trader by John F. Ehlers (intermediate)
  • Cybernetic Analysis for Stocks and Futures by John F. Ehlers (intermediate)
  • Cycle Analytics for Traders by John F. Ehlers (beginner)
  • Statistically Sound Indicators for Financial Market Prediction, algorithms in C++ (advanced)
  • The Universal Tactics of Successful Trend Trading (beginner)

4. Strategies

  • Stocks on the Move by Andreas Clen (beginner)
  • Cybernetic Trading Strategies (intermediate)

5. Trading System Development

  • Testing and Tuning Market Trading Systems (intermediate)
  • Permutation and Randomization Tests for Trading System Development, algorithms in C++ (advanced)

6. Essential Skills for Trading

  • Numerical Recipes - The Art of Scientific Computing
  • Assessing and Improving Prediction and Classification
  • Data-Driven Science and Engineering

7. Niche/Miscellaneous Books

  • Technical Analysis for Algorithmic Pattern Recognition
  • Detecting Regime Change in Computational Finance for Data Science, ML and Algorithmic Trading
  • Trading on Sentiment by Peterson

8. Quant Trading

  • Option Volatility and Pricing by Sheldon Natenberg
  • Dynamic Hedging
  • Frequently Asked Questions in Quantitative Finance (Second Edition) by Paul Wilmott
  • Python for Data Analysis
  • Introduction to Linear Algebra
  • Advances in Active Portfolio Management
  • Technical Analysis is Mostly Bullshit

II. Courses

III. Applications

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