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.

Inspiration

Based on statistical finance principles and educational resources from leading quantitative finance literature and academic research.

Important Limitations

The results are theoretical and exclude transaction costs, liquidity issues, or market frictions. This is for educational purposes only - not financial advice.

Key Features & Methodologies
Comprehensive analytical tools for quantitative finance education
Price Analysis

Tracks price movements to identify baseline trends and patterns.

Z-Score

Detects deviations in return differences to spot potential trading signals (e.g., |z| > 2).

3D Distribution

Shows joint probability of returns with Gaussian ellipsoids, reflecting correlation strength.

Rolling Correlation

Computes dynamic correlations over time windows (30, 60, 90 days).

Backtesting

Simulates trading outcomes to estimate theoretical profitability.

Technical Implementation
Built with modern web technologies and financial libraries

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.