| name | ml4t-book-notebooks |
| description | 基于《Machine Learning for Trading》第二版配套 notebooks 实现量化交易策略开发与回测，涵盖多市场金融数据的时间序列机器学习分析。触发场景：(1) 用户要复现书中的机器学习交易策略代码；(2) 用户要将 ML 模型用于 A 股或美股市场预测；(3) 用户要获取金融数据并训练自己的量化模型。 |
| 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-121","compiled_at":"2026-04-22T13:00:59.543591+00:00","capability_markets":"multi-market","capability_activities":"time-series-ml","sop_version":"crystal-compilation-v6.1"} |
ml4t-book-notebooks
I help you build quant strategies on A-share with ZVT — from data fetch to backtest, one flow. Just tell me what you want; I'll write the code, you don't have to dig docs. (Heads up: ZVT natively supports A-share, HK, and crypto. US stocks — stockus_nasdaq_AAPL — are half-baked; don't bother for serious work.)
Pipeline
data_collection -> data_storage -> factor_computation -> target_selection -> trading_execution -> visualization
Top Use Cases (0 total)
Install
bash scripts/install.sh
Execute trigger: When user intent matches intent_router.uc_entries[].positive_terms AND user uses action verb (run/execute/跑/执行/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 (15 total)
AP-TIME-SERIES-ML-001: TimeSeries values array dimensionality mismatchAP-TIME-SERIES-ML-002: Non-floating-point dtype in TimeSeries valuesAP-TIME-SERIES-ML-003: Irregular or non-monotonic time index
All 15 anti-patterns: references/ANTI_PATTERNS.md
Evidence Quality Notice
[QUALITY NOTICE] This crystal was compiled from blueprint finance-bp-121. Evidence verify ratio = 31.8% and audit fail total = 35. Generated results may have uncaptured requirement gaps. Verify critical decisions against source files (LATEST.yaml / LATEST.jsonl).
Reference Files
Compiled by Doramagic crystal-compilation-v6.1 from finance-bp-121 blueprint at 2026-04-22T13:00:59.543591+00:00.
See human_summary.md for non-technical overview.
