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Alphalens Factor Analysis

作者 Tang Weigang · GitHub ↗ · v0.3.3 · MIT-0
cross-platform ✓ 安全检测通过
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当前安装
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版本数
在 OpenClaw 中安装
/install alphalens-factor-analysis
功能描述
分析alpha因子的预测能力与前向收益特征,生成分组收益、IC、换手率等报告,辅助量化策略的因子研究与事件分析。。
使用说明 (SKILL.md)

Alphalens 因子分析 (alphalens-factor-analysis)

分析alpha因子的预测能力与前向收益特征,生成分组收益、IC、换手率等报告,辅助量化策略的因子研究与事件分析。

Pipeline

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

Top Use Cases (6 total)

Documentation Deployment (UC-101)

Automated build and deployment of project documentation to ensure consistent and reproducible documentation releases Triggers: docs, deploy, build

Sphinx Documentation Configuration (UC-102)

Configures the Sphinx documentation system with extensions for Python API documentation, Jupyter notebooks, and mathematical expressions Triggers: sphinx, config, documentation

PyFolio Portfolio Integration (UC-106)

Combines Alphalens factor analysis with PyFolio portfolio analytics to evaluate factor-derived portfolio performance, risk metrics, and tearsheet gene Triggers: pyfolio, integration, portfolio

For all 6 use cases, see references/USE_CASES.md.

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 (25 total)

  • AP-ZVT-183: 除权因子为 inf/NaN 时直接参与乘法导致复权静默失败
  • AP-ZVT-179: 第三方数据接口超限后异常被吞噬,数据静默缺失
  • AP-ZVT-183B: HFQ(后复权)与 QFQ(前复权)K 线表使用错误导致因子计算漂移

All 25 anti-patterns: references/ANTI_PATTERNS.md

Evidence Quality Notice

[QUALITY NOTICE] This crystal was compiled from blueprint finance-bp-120. Evidence verify ratio = 55.2% and audit fail total = 22. 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+ 全量权威 (source-of-truth) 有行为/决策争议时必读
references/ANTI_PATTERNS.md 25 条跨项目反模式 开始实现前
references/WISDOM.md 跨项目精华借鉴 架构决策时
references/CONSTRAINTS.md domain + fatal 约束 规则冲突时
references/USE_CASES.md 全量 KUC-* 业务场景 需要完整示例时
references/LOCKS.md SL-* + preconditions + hints 生成回测/交易代码前
references/COMPONENTS.md AST 组件地图(按 module 拆分) 查 API 时

Compiled by Doramagic crystal-compilation-v6.1 from finance-bp-120 blueprint at 2026-04-22T13:00:58.879278+00:00. See human_summary.md for non-technical overview.

安全使用建议
This is an instruction-only finance blueprint for factor research (Alphalens/ZVT). Before installing/using it: (1) ensure you have a suitable Python environment (the document requests Python 3.12+ and an 'uv' package manager) and that you trust installing/using zvt/alphalens/pyfolio; (2) be prepared to run the precondition commands the skill may instruct (they check for zvt, try get_kdata, and test writing to ZVT_HOME ~/.zvt); (3) review references/LOCKS.md and CONSTRAINTS.md because the skill enforces fatal semantic locks (e.g., no look‑ahead, T+1 rules) which affect trading/backtest behavior; (4) note there is no automated installer — dependencies and data recorders must be installed and run by you; (5) avoid connecting real trading accounts until you review/validate generated trading code and cost/slippage assumptions. If you want, I can list the exact commands the skill will ask you to run and the files it will create so you can inspect them first.
功能分析
Type: OpenClaw Skill Name: alphalens-factor-analysis Version: 0.3.3 The skill bundle is a comprehensive framework for alpha factor analysis using the ZVT quantitative trading library. It contains extensive documentation on quantitative finance best practices, including 25 cross-project anti-patterns (e.g., lookahead bias, survivorship bias) and detailed domain constraints (finance-C-*) designed to prevent common algorithmic errors. The execution protocols in seed.yaml and SKILL.md focus on enforcing data integrity, trading rules (semantic locks like SL-01), and physical plausibility checks (e.g., annual return limits in output_validator). No indicators of data exfiltration, malicious execution, or harmful prompt injection were found; the instructions are strictly aligned with the stated purpose of financial research and backtesting.
能力标签
crypto
能力评估
Purpose & Capability
Name/description (alpha factor analysis, IC, turnover, tear‑sheets) matches the SKILL.md content which references ZVT/Alphalens/PyFolio workflows and backtest/reporting components. Minor mismatch: SKILL.md states 'Requires Python 3.12+ with uv package manager' even though the registry metadata lists no required binaries or install spec — this is a documentation/packaging gap but not a functional inconsistency.
Instruction Scope
SKILL.md is an instruction-only skill that asks the agent to collect market/data choices, run precondition checks (python -c 'import zvt', get_kdata), and may create/check a ~/.zvt (ZVT_HOME) directory. These actions are appropriate for a backtesting/factor workflow. The instructions do not ask the agent to read unrelated system secrets, contact unexpected external endpoints, or exfiltrate data. They do require running Python on the host and touching a user data directory (expected for this domain).
Install Mechanism
No install spec is provided (instruction-only), so nothing will be downloaded or written by an installer. This is lower risk. Note: SKILL.md references Python 3.12+ and an 'uv' package manager but provides no automated install instructions — users must satisfy these dependencies themselves.
Credentials
The skill declares no required environment variables or credentials. The runtime instructions reference ZVT_HOME (used to locate/create ~/.zvt) and check for Python packages (zvt, get_kdata). Those are proportional to a ZVT-based backtesting skill and do not imply access to unrelated secrets.
Persistence & Privilege
always:false (default) and autonomous invocation allowed (platform default). The skill does not request permanent platform presence or modify other skills; preconditions may create/check files under the user's ZVT_HOME, which is normal for a data/recorder workflow.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install alphalens-factor-analysis
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /alphalens-factor-analysis 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.3.3
v0.3.3: bilingual metadata injected. H1 shows Alphalens 因子分析; tagline replaced with skill-specific Chinese hook; tags upgraded to Level 1-4.
v0.3.1
Remove install.sh — knowledge-only bundle. Host AI consumes directly from URL; no user-side installation needed. Fixes ClawHub suspicious flag.
v0.3.0
Doramagic crystal portfolio v0.3.0. Full 5-layer bp-009 standard. github.com/tangweigang-jpg/doramagic-skills
v0.2.0
Doramagic crystal portfolio v0.2.0. Full 5-layer bp-009 standard. github.com/tangweigang-jpg/doramagic-skills
v0.1.0
Doramagic crystal v0.2.0 portfolio. Compiled from finance blueprint. Source: github.com/tangweigang-jpg/doramagic-skills
元数据
Slug alphalens-factor-analysis
版本 0.3.3
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 5
常见问题

Alphalens Factor Analysis 是什么?

分析alpha因子的预测能力与前向收益特征,生成分组收益、IC、换手率等报告,辅助量化策略的因子研究与事件分析。。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 132 次。

如何安装 Alphalens Factor Analysis?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install alphalens-factor-analysis」即可一键安装,无需额外配置。

Alphalens Factor Analysis 是免费的吗?

是的,Alphalens Factor Analysis 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Alphalens Factor Analysis 支持哪些平台?

Alphalens Factor Analysis 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Alphalens Factor Analysis?

由 Tang Weigang(@tangweigang-jpg)开发并维护,当前版本 v0.3.3。

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