🎓 School of Quant Trading
Learn to build profitable trading systems from the ground up
Foundation
Core concepts every quant trader must know
Why Your Backtest Profits Won't Work Live
The gap between theory and reality in trading
The Difference Between a Strategy and an Edge
Why rules alone won't make you profitable
The Overfitting Trap: When Your Backtest Lies to You
Why complex strategies fail and simple ones survive
What You Actually Need to Build a Signals Engine
The realistic infrastructure, costs, and skills behind systematic trading
The Build vs Buy Decision
A framework for deciding what to build yourself versus what to buy or subscribe to
Course Roadmap: What You'll Learn
Complete overview of the entire quant trading course
Data
Alternative data sources that give you an edge
Why Price and Volume Aren't Enough
The information hierarchy in crypto trading
Introduction to Alternative Data
The data that gives you an edge over price-only traders
Open Interest: Reading the Derivatives Market
How to see where the big money is positioned
Funding Rates: The Cost of Being Wrong
How funding reveals overleveraged markets
Liquidation Levels: Where Prices Get Pulled
Why liquidation clusters act as price magnets
Order Flow: Seeing the Invisible
What happens inside each candle
Data Sources: Where to Get This Data
Free and paid options for serious traders
Building Your Data Pipeline
How to collect, store, and process market data
Validation
How to prove your edge is real
Why 90% of Backtests Lie
The gap between backtest fantasy and live trading reality
Lookahead Bias: The Silent Killer
Accidentally using future data to predict the past
Overfitting: Curve Fitting the Past
When your strategy memorizes noise instead of signal
Walk-Forward Validation
The technique that separates hobby backtests from institutional testing
Sample Size: How Many Trades Is Enough?
Why your 10-trade win rate is meaningless
Metrics That Matter (And Ones That Don't)
Win rate is vanity, profit factor is sanity, Sharpe is reality
Stress Testing: Monte Carlo and Beyond
Will your strategy survive a black swan?
Discovery
Finding edges in market data
The Edge Discovery Framework
How to systematically find edges that actually exist
Z-Score Normalization: Speaking One Language
Making every indicator comparable
Regime Filtering: Context Is Everything
Why your strategy only works sometimes
Combining Indicators: The Multi-Factor Approach
Building robust signals from multiple confirmations
Testing Millions of Combinations
How we run massive discovery without drowning in false positives
From Discovery to Production: The Promotion Pipeline
Getting edges from backtest to live trading safely
Risk
Position sizing and risk management
Position Sizing: The Most Important Decision
Why how much you bet matters more than what you bet on
Drawdown Management: Staying in the Game
Surviving the inevitable losing streaks
Correlation and Portfolio Risk
Why diversification in crypto is harder than you think
Stop Losses: Science vs Art
The most controversial topic in trading risk management
Risk Budgeting Across Strategies
Allocating risk when you have multiple edges
Automation
Building and running trading bots
Architecture of a Trading Bot
The building blocks of automated trading systems
Exchange APIs: Connecting to Markets
Understanding the interface between your code and exchanges
Order Execution: Getting Filled
The art and science of translating signals into positions
Error Handling: When Things Go Wrong
Building systems that fail gracefully
Notifications and Monitoring
Keeping eyes on your system 24/7
Testing Without Losing Money
Validating your system before risking capital
Production
Going live and scaling up
The Go-Live Checklist
Everything to verify before flipping the switch
The First 30 Days: What to Watch
Navigating the critical early period of live trading
Continuous Improvement: Iteration Without Overfitting
Evolving your system while maintaining edge integrity
Scaling Up: From Small to Serious
Growing your trading operation responsibly
When to Kill Your System
Recognizing when its time to stop