Project · Creator and maintainer
myfinance
Working through quantitative finance by implementing it: pricing, portfolio analytics, and fundamentals.
Updated
Context
Moving into quantitative work from an engineering background means learning where the assumptions sit, and reading about a method rarely shows that.
Constraint
Finance writing tends to present a result without the conditions that produced it. The only way to find out what a model is sensitive to is to implement it and vary the inputs.
Contribution
I worked through the territory by building it: Monte Carlo option pricing, fundamental analysis with financial ratios and discounted cash flow, market data ingestion from more than one provider, and stock screening.
Approach
Each area is a self-contained experiment rather than a framework, which keeps the assumption being tested visible instead of buried under abstraction.
Outcome
This is a learning repository and reads like one. It is the groundwork behind later quantitative work that had to be rigorous rather than exploratory.
Evidence
The public repository holds the pricing and analysis notebooks, the data-source integrations, the screening code, and a worked single-stock case study.