laibulle

laibulle

Quant - a library to play with quantitative finance

Hello, I am playing with quantitative finance with Elixir. This library is more a way for me to explore and learn in this area and especially with NX. That’s why I decided to write my own library instead of using python. If you are interested in this area or have some expertise in it, please share your feedback

Fetch financial data from multiple providers with universal parameters and identical output schemas for seamless analysis and maximum performance.

:sparkles: Key Features

:bullseye: Universal API Design

  • Standardized Interface: Same parameters work across ALL providers
  • Identical Schemas: Every DataFrame has exactly 12 columns regardless of provider
  • Cross-Asset Ready: Stocks, crypto, forex all use unified structure
  • Provider Agnostic: Switch providers without changing your analysis code

Best regards

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laibulle

laibulle

The readme was written by claude. And also most of the code, I usually write very descriptive markdowns about what I want especially in term of architecture, concepts and how it should be tested. Then I ask AI to created another markdown to plan the development of a specific feature I start iterate with it, function by function. And check every step that are done. I this way the LLM have the context of project between in session.

I double check everything, read the tests and the code. It sometime fails at solving problems or doesn’t follow exaclty the instructions so in this cases I do it myself. But most of the time it is a 10x accelerator.

The biggest downside of this approach is that it doesn’t help me to learn as well as I would about the implementation and understanding of the matematical concepts around finance. But I expect to dig deeper as soon as I will be able to use Quant in “production”.

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