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Quantitative Research
作者
zhengxinjipai
· GitHub ↗
· v1.0.0
4384
总下载
2
收藏
34
当前安装
1
版本数
在 OpenClaw 中安装
/install quantitative-research
功能描述
World-class systematic trading research - backtesting, alpha generation, factor models, statistical arbitrage. Transform hypotheses into edges. Use when "bac...
安全使用建议
Install only if you want quantitative trading research and backtesting guidance. Treat its outputs as educational or analytical support, not financial advice or permission to trade; verify assumptions, data quality, costs, and risk independently before acting.
能力评估
Purpose & Capability
The artifacts consistently describe quantitative trading research, backtesting, alpha validation, factor models, statistical arbitrage, regime testing, and transaction-cost modeling. The included examples are advisory research patterns, not live execution workflows.
Instruction Scope
The frontmatter and reference detection patterns include broad terms such as alpha, signal, predict, factor, regime, historical, and download. That can cause over-activation or overly finance-specific advice, but the resulting behavior remains domain guidance rather than privileged action.
Install Mechanism
The package contains Markdown reference files and a small skill.json only. No executable scripts, installer commands, dependency installation, binaries, or shell hooks are present.
Credentials
The skill does not request API keys, broker credentials, local profile/session stores, private data indexing, network access, or filesystem access beyond reading its bundled references.
Persistence & Privilege
No persistence, background worker, memory storage, privilege escalation, account mutation, or autonomous trading behavior is evidenced in the artifacts.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install quantitative-research - 安装完成后，直接呼叫该 Skill 的名称或使用
/quantitative-research触发 - 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
v1.0.0
Quantitative Research Skill v1.0.0
- Initial release of quantitative trading research skill.
- Provides expertise in backtesting, alpha generation, factor models, and statistical arbitrage.
- Skill includes detailed personality, contrarian insights, and hard-earned “battle scars” from systematic trading experience.
- Mandates strict grounding in provided reference files for all advice (patterns, failure cases, validations).
- Responds to requests involving terms like backtest, alpha, factor model, statistical arbitrage, mean reversion, momentum, and regime detection.
元数据
常见问题
Quantitative Research 是什么？
World-class systematic trading research - backtesting, alpha generation, factor models, statistical arbitrage. Transform hypotheses into edges. Use when "bac... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 4384 次。
如何安装 Quantitative Research？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install quantitative-research」即可一键安装，无需额外配置。
Quantitative Research 是免费的吗？
是的，Quantitative Research 完全免费（开源免费），可自由下载、安装和使用。
Quantitative Research 支持哪些平台？
Quantitative Research 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 Quantitative Research？
由 zhengxinjipai（@zhengxinjipai）开发并维护，当前版本 v1.0.0。
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