Quantitative Research Hub
Design auditable research workflows, evaluate statistical factors, handle market data feeds, and guard against biases.
30 learning resources across 3 surfaces
Featured Guide
Structured Lessons
Key Concepts & Terms
Glossary
What Is a Quantitative Factor?
Glossary
What Is an Adjusted Price?
Glossary
What Is Data Snooping?
Glossary
What Is Reproducibility in Financial Research?
Glossary
What Is Training Data in Trading? Why a Rule's Sample Decides Its Meaning
Glossary
What Is Overfitting in Backtesting? Fitting Noise, Not a Pattern
Glossary
What Is Look-Ahead Bias? Using Information That Was Not Available Yet
Glossary
What Is Data Leakage? When Future Information Seeps Into a Backtest
Glossary
What Is the Momentum Factor? Cross-Sectional Relative Strength
Glossary
What Is the Value Factor? Systematic Valuation Discounting
Glossary
What Is Data Provenance? Tracking the Origin of Financial Data
Glossary
What Is a Research Audit Trail? Transparent Trading Documentation
Glossary
What Is OHLCV? The Five Pillars of Candlestick Data
Glossary
What Is Tick Data? Granular Trade-by-Trade Microstructure
In-Depth Articles
Market Analysis
Value Factor vs Traditional Value Investing: Systematic Multiples vs Moat Analysis
Market Analysis
What Is Factor Crowding? How Popular Strategies Sow Their Own Reversals
Quant & AI
Look-Ahead Bias: When Your Backtest Uses Information It Couldn't Have Had
Quant & AI
Walk-Forward Testing: Testing a Strategy on Data It Never Saw
Quant & AI
Why Backtest Results Differ From Live Trading: The Gap No Chart Shows
Trading Systems
OHLCV vs Tick Data: What Is the Difference and Which Do You Need?
Trading Systems
REST API vs WebSocket for Market Data: Which Pipeline Fits Your Trading?
Trading Systems
Adjusted Close vs Close Price: Why Using the Wrong One Ruins Backtests
Market Analysis
Trading Research Notebook Template: How to Document Strategies That Can Be Audited
Market Analysis
Data Provenance in Financial Research: Why Untracked CSVs Ruin Strategies
Market Analysis