Advanced Financial Ml

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📖 技能介紹


name: advanced-financial-ml description: |- MlFinLab 提供金融機器學習高階實現,包括資訊驅動 bars(tick/volume/dollar/imbalance bars)、分數階差分和回測工具,支援多市場因子研究與策略驗證。 license: Proprietary. See LICENSE.txt in project root. compatibility: Designed for Doramagic-host ecosystem (Claude Code / openclaw / Cursor). Requires Python 3.12+ with uv package manager. metadata: version: "v6.1" blueprint_id: "finance-bp-115" compiled_at: "2026-04-22T13:00:55.567727+00:00" capability_markets: "multi-market" capability_activities: "backtesting, factor-research" sop_version: "crystal-compilation-v6.1"


金融機器學習 (advanced-financial-ml)

MlFinLab 提供金融機器學習高階實現,包括資訊驅動 bars(tick/volume/dollar/imbalance bars)、分數階差分和回測工具,支援多市場因子研究與策略驗證。

Pipeline

data_collection -> data_storage -> factor_computation -> target_selection -> trading_execution -> visualization

Top Use Cases (1 total)

Sphinx Documentation Configuration (UC-101)

How to configure and generate project documentation using Sphinx autodoc and extensions for API documentation coverage Triggers: documentation, sphinx, autodoc

Execute trigger: When user intent matches intent_router.uc_entries[].positive_terms AND user uses action verb (run/execute/跑/執行/backtest/fetch/collect)

What I'll Ask You

  • Target market: A-share (default), HK, or crypto? (US stocks in ZVT are half-baked — stockus_nasdaq_AAPL exists but coverage is thin)
  • Data source / provider: eastmoney (free, no account), joinquant (account+paid), baostock (free, good history), akshare, or qmt (broker)?
  • Strategy type: MACD golden-cross, MA crossover, volume breakout, fundamental screen, or custom factor?
  • Time range: start_timestamp and end_timestamp for backtest period
  • Target entity IDs: specific stocks (stock_sh_600000) or index components (SZ1000)?

Semantic Locks (Fatal)

ID Rule On Violation
SL-01 Execute sell orders before buy orders in every trading cycle halt
SL-02 Trading signals MUST use next-bar execution (no look-ahead) halt
SL-03 Entity IDs MUST follow format entity_type_exchange_code halt
SL-04 DataFrame index MUST be MultiIndex (entity_id, timestamp) halt
SL-05 TradingSignal MUST have EXACTLY ONE of: position_pct, order_money, order_amount halt
SL-06 filter_result column semantics: True=BUY, False=SELL, None/NaN=NO ACTION halt
SL-07 Transformer MUST run BEFORE Accumulator in factor pipeline halt
SL-08 MACD parameters locked: fast=12, slow=26, signal=9 halt

Full lock definitions: references/LOCKS.md

Top Anti-Patterns (25 total)

  • AP-ZVT-183: 除權因子為 inf/NaN 時直接參與乘法導致復權靜默失敗
  • AP-ZVT-179: 第三方資料介面超限後異常被吞噬,資料靜默缺失
  • AP-ZVT-183B: HFQ(後復權)與 QFQ(前復權)K 線表使用錯誤導致因子計算漂移

All 25 anti-patterns: references/ANTI_PATTERNS.md

小蔥技能站7w4.net,專業的AI技能分享平臺。

Evidence Quality Notice

[QUALITY NOTICE] This crystal was compiled from blueprint finance-bp-115. Evidence verify ratio = 43.7% and audit fail total = 34. Generated results may have uncaptured requirement gaps. Verify critical decisions against source files (LATEST.yaml / LATEST.jsonl).

Reference Files

File Contents When to Load
references/seed.yaml V6+ 全量權威 (source-of-truth) 有行為/決策爭議時必讀
references/ANTI_PATTERNS.md 25 條跨專案反模式 開始實現前
references/WISDOM.md 跨專案精華借鑑 架構決策時
references/CONSTRAINTS.md domain + fatal 約束 規則衝突時
references/USE_CASES.md 全量 KUC-* 業務場景 需要完整示例時
references/LOCKS.md SL-* + preconditions + hints 生成回測/交易程式碼前
references/COMPONENTS.md AST 元件地圖(按 module 拆分) 查 API 時

Compiled by Doramagic crystal-compilation-v6.1 from finance-bp-115 blueprint at 2026-04-22T13:00:55.567727+00:00. See human_summary.md for non-technical overview.

🤖 AI 評測

這個 Skill 內容豐富,涵蓋了量化投資回測的各種坑和約束規則,適合有一定經驗的開發者使用。優點是文件詳細、約束條件多,能幫助避免常見錯誤;不足是證據質量一般,部分內容可能過時或不夠準確,且只有1個示例可參考。整體質量中等偏上,適合做參考但不能完全依賴。

📊 多維度評分

適應性4.1
規範性4.3
有效性4.2
可靠性4.1
可信度4.8

📁 包含檔案 (22 個)

📄 SKILL.md 4.4 KB
📄 _meta.json 140 B
📄 human_summary.md 1.7 KB
📄 references/ANTI_PATTERNS.md 14.8 KB
📄 references/COMPONENTS.md 1.3 KB
📄 references/CONSTRAINTS.md 13.2 KB
📄 references/LOCKS.md 2.4 KB
📄 references/USE_CASES.md 207 B
📄 references/WISDOM.md 4.8 KB
📄 references/components/backtesting_-_statistics.md 584 B
📄 references/components/bet_sizing.md 303 B
📄 references/components/clustering_-_network_generation.md 544 B
📄 references/components/correlation_-_codependence_analysis.md 416 B
📄 references/components/data_ingestion_-_bar_construction.md 432 B
📄 references/components/event_filtering_-_sampling.md 241 B
📄 references/components/feature_engineering_-_importance.md 647 B
📄 references/components/model_training_with_sequential_bootstrap.md 602 B
📄 references/components/sample_weighting_-_uniqueness.md 447 B
📄 references/components/structural_break_detection.md 183 B
📄 references/components/synthetic_data_generation.md 419 B
📄 references/components/triple_barrier_labeling_-_meta-labeling.md 637 B
📄 references/seed.yaml 315.3 KB