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Use when computing the 5D Z-Scored Upper Breakout factor from user-supplied real OHLCV data or reviewing its bundled real-data validation metrics.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Use when an agent needs a verified library of directional OHLCV alpha factor Skills for trend, breakout, reversal, channel-position, or price-direction research across A-share and US equity samples.
Use when computing the 5D Z-Scored Return Momentum factor from user-supplied real OHLCV data or reviewing its bundled real-data validation metrics.
Use when computing the 5D Z-Scored Skip-Period Momentum factor from user-supplied real OHLCV data or reviewing its bundled real-data validation metrics.
Use when computing the 5D Z-Scored Return Reversal factor from user-supplied real OHLCV data or reviewing its bundled real-data validation metrics.
Use when computing the 5D Z-Scored SMA Gap factor from user-supplied real OHLCV data or reviewing its bundled real-data validation metrics.
Use when computing the 5D Z-Scored EMA Gap factor from user-supplied real OHLCV data or reviewing its bundled real-data validation metrics.
| name | quant-real-factor-5d-z-scored-upper-breakout |
| description | Use when computing the 5D Z-Scored Upper Breakout factor from user-supplied real OHLCV data or reviewing its bundled real-data validation metrics. |
| metadata | {"organization":"QuantSkills","organization_url":"https://github.com/quantskills","repository":"skill-quant-factor-directional-alpha","repository_url":"https://github.com/quantskills/skill-quant-factor-directional-alpha","collection":"directional-alpha","factor_id":"R009","category":"Breakout","license":"GPL-3.0-only","copyright":"Copyright (C) 2026 QuantSkills"} |
Use this Skill to compute 5日标准化上轨突破 / 5D Z-Scored Upper Breakout from caller-provided OHLCV data.
pandas.DataFrame with open, high, low, close, volume; include date and symbol for cross-sectional research.scripts/factor.py::compute_factor(df) to compute the factor column.generate_signals(df) for a simple rank-based long/short signal.validation_real/report.md before using the factor in a model.pandas and numpy.