How to leverage Python?

Using Python for Tradevesting

When I started investing in the stock market, one of my advantages was my background as a data engineer and data scientist. This made me comfortable using Python to simplify and automate tasks.

Python is a programming language that’s really easy to learn and use. It helps you write simple code to do things like collect data, perform calculations, and even create charts automatically.

In the stock market, Python can be used to quantify data (turning numbers into useful insights) and automate tasks like getting stock prices, calculating financial metrics, or spotting trends in charts. Instead of doing everything manually, Python does the heavy lifting for you quickly and accurately.

Knowing Python can make your work in the stock market a lot easier by helping you quantify and automate tasks related to both fundamental and technical analysis.

How Python Helps with Fundamental Data?

Let’s say you’re using Screener to get information like sales, profits, PE ratio, ROE, ROCE, and debt-to-equity ratios. Doing this manually for multiple stocks takes a lot of time. With Python, you can:

• Automate the collection of this data.
• Write scripts to pull these metrics from Screener for many stocks at once.
• Use Pandas (a Python library) to organize the data, perform calculations, and identify stocks that meet your criteria (like a specific debt-to-equity ratio).

How Python Helps with Technical Data?

For technical analysis, you might look at things like candlestick patterns, moving averages, and RSI using data from Yahoo Finance. Again, instead of doing this manually, Python helps by:

• Fetching the stock price data automatically.
• Using libraries like TA-Lib to calculate technical indicators like moving averages or RSI.
• Visualizing the data with Matplotlib so you can quickly spot trends or patterns in charts.

By combining these two pieces, you can build a system that automatically gathers the data you need for your Tradevesting strategy and gives you clear, actionable insights, saving time and effort.

If you loved this story, please feel free to check my other articles on this topic here: https://ankit-rathi.github.io/tradevesting/

Ankit Rathi is a data techie and weekend tradevestor. His interest lies primarily in building end-to-end data applications/products and making money in stock market using Tradevesting methodology.