القائمة
Use when computing the 5D Delta Dual EMA Gap factor from user-supplied real OHLCV data or reviewing its bundled real-data validation metrics.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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-delta-dual-ema-gap |
| description | Use when computing the 5D Delta Dual EMA Gap 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":"R039","category":"Trend","license":"GPL-3.0-only","copyright":"Copyright (C) 2026 QuantSkills"} |
Use this Skill to compute 5日变化双EMA趋势差 / 5D Delta Dual EMA Gap 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.