Mathematically rigorous
We state assumptions clearly and show where a method works, where it breaks and why that distinction matters.
about quantint
Turning quantitative thinking into practical knowledge.
We approach financial markets through data, mathematics and working code — not intuition alone.
quantint is an independent research and publishing platform bridging quantitative finance and data science. We unpack complex models without losing their substance and make every argument possible to follow.
10published research pieces
6core subject areas
2publishing languages
100%transparent methodology
why we exist
Better questions, more robust models.
Quantitative-finance material often stops at theory or presents code without context. We bring both into one research workflow: from assumption to model, from model to test, and from test to interpretation.
Our goal is not to hand out trading signals. It is to help readers challenge a claim, rebuild a model and understand the limits of its conclusions.
publishing principles
Three standards behind every piece.
No matter how complex the topic, we do not trade away research quality or clarity.
Verifiable with code
We do more than describe results: data steps, formulas and working implementations are presented together.
Accessible by design
We preserve technical accuracy while building intuition through visuals and carefully sequenced examples.
how we work
From research question to published work.
- 01
Define the question
We begin with a measurable, falsifiable question grounded in a real market problem.
- 02
Study literature and data
Academic evidence, data quality and the method's assumptions are evaluated together.
- 03
Build and pressure-test
We reproduce the model and test leakage, bias, transaction costs and robustness.
- 04
Publish openly and update
Limitations are published alongside findings, and the work is revised when new evidence appears.
fields of work
A map from theory to markets.
From statistical foundations to production-quality Python, each subject gets the same research discipline.
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transparency note
Research, not investment advice.
All content is for education and research. Nothing published is personal investment advice or a promise of returns. We commit to stating data sources, methods, conflicts of interest and material limitations clearly.