About Quant Visualizer
This tool presents complex mathematical ideas in quantitative finance using educational models and historical stock data. It helps visualize key statistical concepts in a simple, interactive way.
Based on statistical finance principles and educational resources from leading quantitative finance literature and academic research.
The results are theoretical and exclude transaction costs, liquidity issues, or market frictions. This is for educational purposes only - not financial advice.
Tracks price movements to identify baseline trends and patterns.
Detects deviations in return differences to spot potential trading signals (e.g., |z| > 2).
Shows joint probability of returns with Gaussian ellipsoids, reflecting correlation strength.
Computes dynamic correlations over time windows (30, 60, 90 days).
Simulates trading outcomes to estimate theoretical profitability.
Technology Stack: Python, Next.js, React, TypeScript, Tailwind CSS, Recharts for visualizations, and various financial data APIs. Built a Next.js + FastAPI application to analyze stock pair trading strategies.
Data Sources: Historical stock data from reliable financial APIs, processed using statistical methods including NumPy-equivalent calculations and SciPy-style statistical functions.
Ready to explore quantitative analysis? Visit the Analytics Dashboard to get started.