Want to learn how to write code to be a more dynamic professional.
Which had the best application for the business world / is used by quantitative trading firms.
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Python is your best bet for becoming a more dynamic professional in the business world, especially in quantitative trading and finance. Based on the most helpful WSO content:
Python's Versatility: Python is highly flexible and widely used in finance for tasks like data analysis, backtesting trading strategies, and automating workflows. Its libraries like Pandas (data manipulation), NumPy (numerical computing), and Seaborn/Matplotlib (visualization) make it a powerhouse for financial applications.
Quantitative Trading: Python is often used for writing trading algorithms and backtesting strategies. While high-frequency trading firms may rely on C++ for speed, Python is much easier to learn and implement for most quantitative tasks.
SQL for Data Retrieval: While Python is great for analysis, SQL is essential for retrieving and organizing data from databases. Combining Python with SQL allows you to import and manipulate data efficiently.
Other Languages: If you're looking to expand beyond Python, R is another option for data manipulation and statistical analysis, though it has a steeper learning curve. Haskell is praised for its mathematical rigor but is less common in the business world.
For a beginner aiming to be dynamic and versatile, start with Python. It’s easy to learn, has a vast community, and is highly applicable across industries. You can later complement it with SQL and explore other languages like R or Haskell if needed.
Sources: Programming/Technical Skills for Finance: SQL and Python, Programming/Technical Skills for Finance: SQL and Python, WSO Python / Machine Learning Courses - NOW AVAILABLE, BAML Front-office quant vs Prop Shop Trading, 0 to pseudo quant real quick - analytical skills for juniors with finance background
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