Institutional-grade analysis,
built in the open.
Equity.Finance combines quantitative finance with modern engineering. No black boxes. No paywalls. No compromises on rigor.
While studying Financial Management at Nyenrode Business University, I noticed a disconnect.
The models we studied in class — DCF, LBO, portfolio theory — were elegant in textbooks but clunky in practice. Analysts at top firms were still building critical models in sprawling Excel sheets, copy-pasting between tools, and running simulations by hand.
I started building. First small Python scripts to automate DCF models. Then a portfolio optimizer. Then a full trading simulator with technical analysis. Equity.Finance became the place where all of these tools live — open, interactive, and built with the same rigor taught in classrooms but powered by modern technology.
This isn't a startup selling software. It's a working demonstration of what happens when you combine quantitative finance with engineering.
What we believe
Transparency
Every calculation is visible. Every assumption is editable. If you can't see how the number was made, you can't trust it — and we can't either.
Rigor
The models here are the same ones used by analysts at institutional shops. No simplifications that would mislead, no shortcuts that would break under pressure.
Independence
No sell-side incentives. No affiliate links. No sponsored content. The analysis is the product, and it stays independent of who it happens to flatter.
Open methods
The methodology is documented, the code is inspectable, and the limitations are stated up front. We would rather lose a reader than mislead one.
“The gap between what's taught in the classroom and what's practiced on the desk is where this project lives.”
— Stijn Koster, Founder
How we work
Research
Every idea starts with reading, data gathering, and literature review. We anchor each analysis in verifiable facts before building any model on top of it.
Browse research →Model
The research is translated into a working tool — a DCF, an LBO, a backtest, a portfolio simulation. The model is the artifact that makes the reasoning testable.
Open the lab →Publish
The model, the data, and the conclusions are published together. Readers can trace every claim back to its source and rebuild the analysis themselves.
Example walkthrough →Methodology
The Journey
The Disconnect
Studying Financial Management at Nyenrode, noticing the gap between elegant textbook models and clunky industry practice. The idea: what if institutional-grade tools were accessible to everyone?
First DCF Automation →
Python scripts to automate DCF models and sensitivity analysis. What took hours in Excel took seconds. The foundation for every valuation tool that followed.
Portfolio Optimizer →
Built a full portfolio optimization tool with efficient frontier calculation, Monte Carlo simulation, and Black-Litterman integration.
Trading Simulator →
Real-time charting with technical indicators, backtesting engine, and strategy analysis. RSI, MACD, SMA crossover — all interactive.
LBO & Deal Analysis →
Leveraged buyout modeling with debt scheduling and sensitivity analysis. M&A deal screening with comparable transaction data.
Equity.Finance
All tools published as an open, interactive platform. Live market data via Yahoo Finance. Deployed on Vercel. Institutional-grade, freely accessible.
What Makes This Different
Real Analytical Tools
Not simplified calculators — these are the models used by analysts and portfolio managers. Three-stage DCF, efficient frontier optimization, Monte Carlo simulation, Black-Litterman.
Built by Someone Who Uses Them
Every tool is designed from first-hand experience with financial analysis. Grounded in the academic frameworks taught at Nyenrode, pressure-tested against real market data.
Educational by Design
Strategy explanations, parameter guidance, and interconnected tools that teach as you use them. Learn by doing, not by reading.