Phase 12 // Course Syllabus Chapter
Backtesting in TradingView — Strategy Tester, Inputs & Monte Carlo.
Part of our masterclass path. We systematically cover risk, logic, and mechanics to build professional edge.
Floor Tier Access 30 min read / 18 min video
01_Curriculum_Brief
What is covered in this chapter
Automated Backtesting and Optimization
Once you code your strategy rules in Pine Script, you can run them against a decade of tick data in seconds using TradingView's Strategy Tester. This module covers how to interpret the results and stress-test performance.
Backtest Note: Do not fall into the trap of over-optimizing parameters (curve fitting) to achieve a perfect backtest curve. We cover manual verification workflows; check out the Manual Backtesting workflow to compare results.
The Strategy Metrics
We analyze profit factor, drawdown, and expectancy, and show you how to export the trade list to run Monte Carlo simulations.
Interactive Lesson Locked
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Phase 12 Chapters
01What AI Can and Cannot Do in Trading — Separating Signal From Hype02Using Claude and GPT as Pre-Trade Research Tools03Building a Custom AI Trade Journal Prompt System04Automating Your Morning Briefing With AI-Scraped Macro Data05Pine Script Fundamentals — Coding Your Strategy Rules in TradingView06Backtesting in TradingView — Strategy Tester, Inputs & Monte Carlo07Building an AI Market Scanner — Prompts, Filters & Alert Logic08Creating a Personal AI Trading Playbook09Automating Your Trade Log — CSV to AI Analysis Pipeline10Using AI to Detect Emotional Patterns in Your Trading History11Advanced — Connecting TradingView Webhooks to Automated Systems12Ethics and Risk of Automation — When to Keep the Human in the Loop