Algorithmic Indicator Calibration Lab
Backtest and calibrate oscillator parameters across diverse volatility regimes and asset classes.
Program Specifications
Admissions require a 20-minute diagnostic intake interview.
Who This Coaching Is For
Systematic traders, programmers, and quantitative analysts seeking empirical indicator optimization without curve-fitting.
The Concrete Result
Build robust, adaptive indicator parameters that automatically adjust for high-volatility events vs quiet consolidation ranges.
Curriculum & Technical Scope
- • Adaptive lookback periods using Average True Range (ATR) multipliers
- • Avoiding over-optimization and curve-fitting traps in backtesting
- • Walk-forward statistical validation of momentum signals
- • Building quantitative scoring models for multi-indicator confluence
What Is Included
- ✓ 6 In-depth quantitative sessions with code walkthroughs (Python / Pine Script)
- ✓ Open-source calibration spreadsheets and backtesting templates
- ✓ One 45-minute private code/strategy review with Daniel Vance
Explicit Program Exclusions
- ✗ No automated trading bot hosting or server administration
Step-by-Step Delivery Process
How you progress from diagnostic calibration to independent trade execution discipline.
Module 1
Mathematical framework of oscillator responsiveness vs. lag.
Module 2
Volatility-adaptive calibration techniques and regime filtering.
Module 3
Out-of-sample testing protocols and practical strategy deployment.
Preparation & Prerequisites
Basic familiarity with spreadsheet calculations or scripting (Pine Script / Python) is beneficial.
Cohort Constraints & Seat Limits
Limited to 12 participants per quantitative cohort.
Ready to Apply for this Program?
Submit a technical background inquiry to join the quantitative cohort.
Submit Diagnostic Inquiry