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Merge pull request #122 from PyP-Quant/idea/061-eurusd-carry-aware-trend-overlay-1m
Add idea 061: EURUSD carry-aware trend overlay 1m
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# Idea 061: EURUSD Carry-aware trend overlay
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## Summary
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Document a PyP Quant strategy candidate for EURUSD on 1m candles using a LogisticRegression approach focused on carry-aware trend overlay.
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## Market Hypothesis
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EURUSD may show repeatable behavior when carry-aware trend overlay conditions align with volatility, trend, and recent structure filters. The first implementation should stay conservative and treat this as an educational research candidate, not a production trading recommendation.
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## Candidate Features
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- Recent return over 3, 6, and 12 bars.
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- ATR-normalized candle range and close location value.
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- Rolling volatility percentile over 50 and 200 bars.
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- Distance from EMA 20, EMA 50, and EMA 200.
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- Session flag or market-hours bucket where applicable.
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- Prior swing high and swing low distance.
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## Label Design
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- Predict whether the forward 1m move exceeds an ATR-normalized threshold.
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- Use neutral labels when the forward return is too small to justify risk.
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- Tune the horizon separately for trend, range, and scalp variants.
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## Risk Controls
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- Require minimum confidence before emitting UP or DOWN.
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- Block signals during abnormal spread, missing candles, or low-liquidity windows.
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- Cap exposure per instrument and stop after a daily drawdown limit.
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- Validate stop-loss and take-profit levels with PPE simulation before live use.
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## Backtest Checklist
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- Compare against HOLD and simple moving-average baselines.
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- Run walk-forward splits with no future leakage.
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- Inspect trade count, profit factor, max drawdown, win rate, and average adverse excursion.
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- Review behavior by session, volatility regime, and weekday.
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## Implementation Notes
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This idea is intentionally Markdown-only. A future template can add `strategy.py`, `quant.config.json`, and a focused README once PPE results justify turning the idea into executable code.
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Closes #121
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