Algorithmic Strategy
A complete masterclass on building and trading algorithmic strategies used by a 7-figure trader — covering system design, backtesting, execution, and risk management.
Full video breakdownFree access
Strategy Overview
This masterclass covers the complete lifecycle of an algorithmic trading strategy — from idea generation and statistical validation through backtesting, optimization, and live deployment. The focus is on building robust systems that generate consistent returns with minimal drawdown.
Market Focus
Algorithmic strategies discussed span multiple markets including NASDAQ equities, Forex majors, and major crypto pairs. The principles apply universally — what matters is data quality, liquidity, and clearly defined rules.
Timeframes
Strategies range from high-frequency 1-minute systems to daily swing strategies. Each timeframe has different characteristics, costs, and data requirements. The masterclass covers how to choose the right timeframe for your system.
Core Idea
Discretionary traders make decisions based on feel. Algorithmic traders make decisions based on rules. The power of algorithms is removing emotion and being able to backtest across thousands of historical scenarios before risking real capital.
Market Conditions
All algorithms have conditions where they work and conditions where they don’t. The masterclass teaches how to build regime filters that automatically shift the system to cash or defensive positioning during unfavorable conditions.
Strategy Setups
Covered setups include: momentum breakout algorithms, mean reversion overnight holds, cross-asset correlation trades, and machine learning-assisted entry filters. Each is backtested with full statistics.
Trade Breakdown
All positions sized using fixed fractional or Kelly Criterion models. Drawdown limits are hardcoded. The masterclass covers how to build automatic kill switches that pause trading after defined loss thresholds.
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This page is for educational purposes only and is not investment advice. Trading involves substantial risk of loss. Past performance and any figures mentioned in strategy names are not a guarantee of future results.