Optimize Pine Script Scalping
Budget: $10 – $30 USD
I have an existing Pine Script strategy running on TradingView that I use for very short-term, scalping style entries. I need you to deep-dive into historical price data, back-test every adjustable input and uncover the combination that gives the best balance between net profit and drawdown. Pure profit at the cost of huge risk is not acceptable, and neither is a drawdown-free system that barely moves the needle—I want an evidence-backed middle ground.
Beyond parameter tuning, I also want to understand when the script actually performs. Your research should isolate the most favourable trading windows during the day and week so I can schedule alerts only when the edge is strongest.
Deliverables
• A revised set of strategy settings (exact values) that maximises the profit-to-risk profile
• A concise performance report: equity curve, key metrics (net profit, max drawdown, profit factor, win rate) and a short commentary on stability across markets and time-frames tested
• A heat-map or table showing what hours or sessions historically delivered the best results
• The Pine Script file (if any code adjustments were required) with clear comments on what changed
Acceptance criteria
• Back-test must cover at least three years of minute-level data
• Max drawdown no greater than the original while net profit improves meaningfully, or a clear rationale if trade-offs arise
• Replicable results when I run the same settings on my end in TradingView
If you are comfortable extracting robust insights from historical price data and presenting them in a way I can act on immediately, let’s move forward.
Beyond parameter tuning, I also want to understand when the script actually performs. Your research should isolate the most favourable trading windows during the day and week so I can schedule alerts only when the edge is strongest.
Deliverables
• A revised set of strategy settings (exact values) that maximises the profit-to-risk profile
• A concise performance report: equity curve, key metrics (net profit, max drawdown, profit factor, win rate) and a short commentary on stability across markets and time-frames tested
• A heat-map or table showing what hours or sessions historically delivered the best results
• The Pine Script file (if any code adjustments were required) with clear comments on what changed
Acceptance criteria
• Back-test must cover at least three years of minute-level data
• Max drawdown no greater than the original while net profit improves meaningfully, or a clear rationale if trade-offs arise
• Replicable results when I run the same settings on my end in TradingView
If you are comfortable extracting robust insights from historical price data and presenting them in a way I can act on immediately, let’s move forward.