Our Methodology
How we develop, validate, and maintain algorithmic trading systems for consistent performance across market conditions
Core Philosophy
Build robust systems that adapt to changing markets without constant intervention
Simplicity
Clear logic over complexity. If a system can't be explained simply, it's probably over-engineered.
Robustness
Performance across market conditions. Bull markets, bear markets, high volatility, low volatility.
Diversification
Multiple uncorrelated systems across timeframes and instruments reduce portfolio volatility.
Development Process
From concept to live trading in five rigorous stages
Hypothesis
Identify repeatable market behavior grounded in mechanics, not just patterns.
Development
Translate logic into clean EasyLanguage code with sensible defaults.
Backtesting
Test across multiple years and market regimes. Avoid curve-fitting.
Forward Test
Run live for several months on unseen data before publishing.
Live Trading
Publish with full transparency. Track every trade daily.
Validation Criteria
- Consistent multi-year performance
- Profit factor above 1.3
- Manageable drawdowns
- Statistical significance (100+ trades)
Red Flags We Avoid
- Performance from outlier years
- Too few trades for significance
- Excessive parameters
- Unrealistic assumptions
Our rule: A system must demonstrate profitable forward performance before being added to the portfolio. If the core logic doesn't work with simple parameters, adding complexity won't fix it.
Two Trading Approaches
Different strategies for different market opportunities
Day Trading
Systems 1-4, 6, 7, 10
Close all positions by end of session, eliminating overnight risk.
Each day has its own optimized parameters
Swing Trading
Systems 5, 8, 9
Hold positions for days or weeks, capturing larger price moves.
Different parameters for each market regime
Day Trading Implementation
Each day trading system consists of 5 individual scripts (Mon-Fri). Save each script separately in TradeStation or MultiCharts, then apply all 5 to the same chart. Each script activates only on its designated weekday, allowing unified performance tracking while maintaining weekday-specific optimization.
Why Weekday Optimization?
Each weekday has distinct market dynamics that affect trading behavior
Markets don't behave uniformly throughout the week. Institutional flows, economic data releases, options activity, and trader psychology create predictable patterns that vary by day. Rather than using one-size-fits-all parameters, we optimize each weekday separately while maintaining the same core trading logic.
Week positioning as institutions establish directional bias for the week.
Follow-through day where Monday's moves either continue or reverse.
FOMC announcement days create elevated volatility 8 times per year.
Economic data releases including weekly jobless claims and other indicators.
Weekly options expiration creates unique price dynamics and positioning.
What varies by weekday:
Risk Management
Every system includes built-in stop losses and take profits
Percentage-Based
Most systems use percentage-based stops relative to entry price. For example, a 1% stop loss on a long entry at $15,000 would exit at $14,850.
ATR-Based
Some systems use ATR (Average True Range) multipliers for dynamic stops that adapt to current volatility. Higher volatility = wider stops.
Session Exits
Day trading systems also include time-based session exits. If a position hasn't hit its stop or target by a specified time (typically 3:00-4:00 PM ET), it's closed at market to avoid overnight exposure.
Annual Parameter Updates
Fine-tuning parameters to adapt to evolving market conditions
Markets evolve. What worked optimally two years ago may not be optimal today. We address this through annual parameter reviews, typically conducted once per year.
What We Update
- Entry and exit thresholds
- Indicator periods and lookbacks
- Stop loss and take profit levels
- Time windows for entries
- Day-specific parameters
What Stays the Same
- Core trading logic
- Entry and exit methodology
- Indicators used
- Risk management approach
- Overall system structure
Why this matters: Parameter fine-tuning allows systems to remain effective as market dynamics shift, without requiring a complete redesign. The core edge remains intact while adapting to current conditions.
Full Transparency
Every trade is logged and published — verify performance yourself
See the Results
Explore the performance of all 10 systems built using this methodology. View equity curves, drawdowns, and detailed trade statistics.