FUSA500IDXUSD 240 MINUTE.csv FUSA500IDXUSD 60 MINUTE (1).csv Fquantitative-trading-strategy.zip
https://v0.app/chat/quantitative-trading-strategy-s5FqKUjxxnm
Finish from where we left off
Mandatory Performance Requirements
Every candidate strategy must satisfy:
- Profit Factor ≥ 1.30
- Win Rate ≥ 40%
- Minimum 50 completed trades per year on average across the entire dataset.
- Positive expectancy.
- Large statistical sample.
- Profitable in every individual calendar year contained in the supplied historical dataset.
- Stable yearly equity growth.
- Robust across different market regimes.
- Low parameter sensitivity.
If no strategy satisfies every requirement:
- Continue researching new statistical edges.
- Continue generating new hypotheses.
- Continue testing alternative execution logic.
- Continue exploring different market behaviors.
Only after exhausting genuinely different statistical ideas may you introduce additional filters or refinements.
Any added filter must improve:
- Out-of-sample performance.
- Walk-forward performance.
- Robustness.
Never add filters whose only purpose is increasing historical Profit Factor.
If no statistically honest solution exists after exhaustive research, explicitly state that no such strategy exists.
Research Process
Continue searching until one of the following occurs:
- A strategy satisfies every requirement.
- Exhaustive statistical research indicates that no such strategy exists.
Do not stop after finding the first profitable strategy.
Keep searching for stronger and more robust alternatives.
Optimization Objective
The objective is not to maximize historical Profit Factor.
The objective is to maximize the probability that the strategy survives real live trading.
When two candidate strategies achieve similar performance, always prefer the one with:
- Lower execution costs.
- Higher average profit per trade after all costs.
- Better walk-forward performance.
- Better out-of-sample performance.
- Lower parameter sensitivity.
- More stable yearly returns.
- Greater robustness across different market regimes.
Always prioritize long-term robustness over historical optimization.
Output Efficiency
Prioritize research over presentation.
Generate only lightweight reports.
Avoid:
- Fancy dashboards.
- Decorative charts.
- Interactive UI.
- Complex layouts.
- Large visualizations.
- Animations.
- Excessive formatting.
- Repeated tables.
- Any non-essential graphics.
Use simple markdown and compact tables only.
Allocate the maximum possible computation, context, and tokens to:
- Statistical discovery.
- Edge generation.
- Validation.
- Robustness testing.
- Portfolio construction (if applicable).
- Pine Script generation.
Minimize token usage devoted to presentation.
Deliverables
Provide only:
- Research summary.
- Statistical findings.
- Final strategy (or portfolio if appropriate).
- Validation results.
- Walk-forward results.
- Out-of-sample results.
- Monte Carlo results.
- Execution-cost analysis.
- Year-by-year performance table.
- Pine Script Version 6.
- Essential implementation notes.
Do not generate dashboards, charts, UI components, or visual reports unless explicitly requested.