PythonInvest-basic-fin-analysis

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Use Your Computer to Make Informed Decisions in Stock Trading

INTRO

These articles are intended to guide a delevoper, analyst, or an individual investor with some programming experience on how to use Python and Google Colab to get a financial data, analyse it, and test the investment hypothesis at scale

The Colab code is used in the blog PythonInvest. Please refer to the Website or posts on Medium to get the most detailed explanation.

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MEDIUM POSTS

• :one:  Part 1: Python Environment
• :two:  Part 2: Exploring Finance APIs
• :three:  Part 3: Sentiment Analysis of Financial News
• :four:  Part 4: Scraping Earnings Per Share (EPS)
• :five:  Part 5: Developing a Short Term Investment Strategy Based on Earnings-Per-Share(EPS) Data
• :six:  Part 6: Boom of IPOs in 2020
• 7️⃣  Part 7: Comparing IPOs from late 2020 vs. early 2021
• 8️⃣  Part 8: Practical Portfolio Optimisation
• 9️⃣  Part 9: Macroeconomic Indicators Affecting Stock Market
• :one::zero:  Part 10: Passive Investing with ETFs in Europe
• :one::one:  Part 11: 2023 Update - Passive Investing with ETFs in Europe
• :one::two:  Part 12: All Weather Portfolio (of ETFs) with Crypto
• :one::three:  Part 13: Leveraging OpenAI's API for Financial News Summarization

FOLDERS

colab_notebooks All notebooks with the code are published in the colab_notebooks folder. Please copy them and try to run. I'm happy to hear any idea to improve the code or just that you find this work useful.

static Some colab notebooks have dumps of graphs to the JSON format (Plotly), which is inserted to the website.

yt_videos_colabs Sometimes there is a redacted version (nomally, easier and smaller) of a main colab from an article, that I use in videos on the PythonInvest YouTube channel.

Cheers,
PythonInvest team