Learn Python For Commodity Trading And Data Analysis (With Free PDFs)

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Are you thinking of learning python for commodity trading? It’s a great idea. Whether for data analysis, trading backtesting, or risk management – you’ll be hedged.

Python For Commodity Trading

Data analysis is key to improve decision making.

Whether you want to price options, back-test trading models, or implement a trading algorithm, Python will be a fantastic option.

Why Python?

Python is the language of data.

Python is perfect for data analysis because it is easy-to-learn, compact, and an industry standard.

Python is commonly used for data science at prototyping and even at some production stages in hedge funds.

Start Learning Python Online

Nowadays the internet offers excellent learning platforms to get into python.

The best resources for learning python online are:

Beginner Online Material

  • Codecademy
    Fantastic learning platform (free / ~$20/month).
    Learn data science and web development with Javascript frameworks such as React, Angular, Express, Node, and MongoDB.
  • DataCamp
    Slightly higher quality platform focused exclusively on data science. (free / ~$40$ per month).
    Learn data science with Python or R (some still use it)

Advanced Material

Practise Python With Market Data

  • Quantopian
    Quantopian is the best possible playground for algo trading.
    Quantopian offers free database access and demo tests so that you can learn the skills to become a quant trader.

Reading List

Beginner Python Books

  • Think Python (Free PDF / Amazon)
    New to Python? Start with this basic manual.
  • Learning Python (Amazon)
    Introductory text to the main aspects of python.

Data Science Python Books

  • Python for Data Analysis (Amazon)
    Overview of the main techniques including using pandas, numpy, and ipython.
  • Python Data Science Handbook (Amazon)
    Useful manual for python data scientists

Advanced Python Books

  • The Hitchhiker’s Guide to Python (Amazon)
    Learn to code “phytonically“, ie, the best practise for maximal readability and effectiveness.
  • Fluent Python (Amazon)
    Learn to optimise your code and make it more efficient and effective.
  • Python Cookbook (Amazon)
    Good book on optimal code.

Data Science Books

  • Data Science From Scratch (Amazon)
    Introductory text that gives a broad overview of the process. Recommended.
  • Doing Data Science (Amazon)
    Fantastic book, yet compiled in R.

Statistics & Probability Books

  • Think Stats (Free PDF / Amazon)
    Fantastical brief intro to statistics and probability with Python.
  • Think Bayes (Free PDF / Amazon)
    Introduction to Bayesian statistics using Python.
  • Practical Statistics For Data Scientists (Amazon)

Complexity Theory & Signal Processing Books

  • Think Complexity (Free PDF / Amazon)
    Learn about complexity – the intersection of math, computer science, and natural sciences.
  • Think DSP (Digital Signal Processing) (Free PDF / Amazon)
    Learn how learn from digital signals by processing them statistically.

Machine Learning

  • Introduction to Machine Learning With Python (Amazon)
    Start here your adventure in Machine Learning!
  • Hands-On Machine Learning with Scikit-Learn and TensorFlow (Amazon)
    Impressive book for those who want to bring their python skills to the next level with AI/ML.
  • Fundamentals of Deep Learning (Amazon)
    Advanced material for proficient coders.

Careers for Python Coders / Quants

The most common positions for those with coding skills:

RELATED: Curated Commodity Trading Jobs

  • Data Analyst
    A data analyst will examine data and come up with actionable business insights.
  • Quant Analyst
    A quant analyst will most likely be looking at derivatives pricing to ensure risks are controlled.
  • Quant Trader
    A quant trader will ideate and partially implement trading strategies based on quantitative criteria.
  • Quant Developer
    Most likely you’ll be adapting trading strategies and translating from python/R to production code like C++.

Are you ready to start your quant career?

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