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Bt Portfolio Backtest

by Tang Weigang · GitHub ↗ · v0.3.3 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install bt-portfolio-backtest
Description
使用 bt 框架构建和回测多策略投资组合，支持风险平价、等风险贡献、逆波动率加权等组合构建方法，以及政府债券滚动交易的模拟回测。
README (SKILL.md)

bt 组合回测 (bt-portfolio-backtest)

使用 bt 框架构建和回测多策略投资组合，支持风险平价、等风险贡献、逆波动率加权等组合构建方法，以及政府债券滚动交易的模拟回测。

Pipeline

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

Top Use Cases (20 total)

Buy and Hold Monthly Rebalancing Strategy (UC-101)

Implements a passive buy-and-hold strategy with monthly rebalancing to fixed target weights, demonstrating core backtesting framework capabilities Triggers: buy and hold, monthly rebalance, fixed weights

Equal Risk Contribution Portfolio Construction (UC-102)

Demonstrates Equal Risk Contribution (ERC) portfolio weighting using multivariate normal returns and covariance matrix inputs for risk parity allocati Triggers: equal risk contribution, risk parity, covariance

Fixed Income Government Bond Rolling Strategy (UC-103)

Simulates rolling government bond trading with synthetic price-to-yield calculations and bond lifecycle management for fixed income backtesting Triggers: fixed income, government bonds, rolling bonds

For all 20 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-125. Evidence verify ratio = 10.0% and audit fail total = 14. 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-125 blueprint at 2026-04-22T13:01:02.252610+00:00. See human_summary.md for non-technical overview.

Usage Guidance
This skill is internally inconsistent: it advertises 'bt' usage but its instructions and included artifacts are heavily ZVT/blueprint-centric and expect the agent to check/install zvt and manipulate ~/.zvt. Before installing or invoking it, ask the maintainer to clarify: (1) which framework is actually required (bt or zvt) and provide an explicit install spec; (2) list all required binaries and environment variables (e.g., ZVT_HOME) and any credential needs; (3) confirm whether the skill will run pip installs or write to your home directory. If you proceed, run it in a sandboxed environment, do not supply sensitive credentials, and review any pip install commands and scripts the agent would execute. If you cannot get clarification, treat the skill as untrusted and avoid running its automated precondition/install steps on your main system.
Capability Analysis
Type: OpenClaw Skill Name: bt-portfolio-backtest Version: 0.3.3 The skill bundle is a comprehensive framework for financial portfolio backtesting using the 'bt' and 'zvt' libraries. It contains extensive documentation on domain-specific constraints, anti-patterns, and semantic locks (e.g., SL-01 through SL-12 in SKILL.md and seed.yaml) designed to ensure the AI agent generates valid and reliable trading logic. The installation recipes and dependencies are standard Python finance packages, and there is no evidence of malicious intent, data exfiltration, or harmful prompt injection.
Capability Tags
crypto
Capability Assessment
⚠ Purpose & Capability
Name/description advertise building/backtesting with the 'bt' framework, but SKILL.md, seed.yaml, and many reference files repeatedly mention ZVT, zvt-related preconditions, and a finance blueprint (finance-bp-125). The metadata also requires 'Python 3.12+ with uv package manager' even though the registry entry declares no required binaries or env vars. This mismatch (bt vs ZVT/blueprint, implied dependencies not declared) is disproportionate to the stated purpose and suggests either sloppy composition or embedded unrelated functionality.
⚠ Instruction Scope
Runtime instructions and seed.yaml require the agent to run precondition checks that import zvt, assert ZVT_HOME, touch files in ~/.zvt, and (on failure) run pip install and zvt init commands. SKILL.md also includes fatal 'semantic locks' (strict execution rules) and an execution_protocol that instructs re-reading seed.yaml and running host install recipes. None of these operations were declared in the skill's registry metadata; they access environment/config state beyond a simple 'write-only' helper and could cause the agent to attempt installs, filesystem writes, or network access to data providers.
ℹ Install Mechanism
There is no install spec (instruction-only), which reduces risk from arbitrary downloaded code. However seed.yaml's execution_protocol references install_recipes and package verification steps that are not provided here, and SKILL.md demands a specific Python+package manager environment. The absence of an explicit, consistent install recipe while embedding install instructions in text is inconsistent and worth noting.
ℹ Credentials
Registry reports no required env vars/credentials, yet the instructions reference and validate ZVT_HOME and rely on external data providers (eastmoney, joinquant, qmt, etc.) that may require credentials/accounts. The skill may prompt the agent to run pip installs and create/modify ~/.zvt. Requested environment access is not declared up-front, which is disproportionate to the listed metadata.
ℹ Persistence & Privilege
The skill does not set always:true and is user-invocable, which is appropriate. It does, however, instruct initialization of local data directories (zvt.init_dirs), touching files under ~/.zvt, and mandates re-reading seed.yaml before behavioral decisions (execution_protocol). Those are not global privileges, but they do give the skill potential to modify user-local config/data — the behavior is plausible for backtesting but should be made explicit.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install bt-portfolio-backtest
  3. After installation, invoke the skill by name or use /bt-portfolio-backtest
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.3.3
v0.3.3: bilingual metadata injected. H1 shows bt 组合回测; 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
Metadata
Slug bt-portfolio-backtest
Version 0.3.3
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 4
Frequently Asked Questions

What is Bt Portfolio Backtest?

使用 bt 框架构建和回测多策略投资组合，支持风险平价、等风险贡献、逆波动率加权等组合构建方法，以及政府债券滚动交易的模拟回测。 It is an AI Agent Skill for Claude Code / OpenClaw, with 122 downloads so far.

How do I install Bt Portfolio Backtest?

Run "/install bt-portfolio-backtest" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Bt Portfolio Backtest free?

Yes, Bt Portfolio Backtest is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Bt Portfolio Backtest support?

Bt Portfolio Backtest is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Bt Portfolio Backtest?

It is built and maintained by Tang Weigang (@tangweigang-jpg); the current version is v0.3.3.

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