What makes A Stock Quantitative Screener notable?

1.4K downloads. Trust evidence available

How should A Stock Quantitative Screener be evaluated before use?

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A Stock Quantitative Screener

量化筛选A股潜力股，结合资金流、技术指标、趋势强度、基本面和筹码集中度，提供多角度投资建议与风险提示。 Skill: A Stock Quantitative Screener Owner: xiaobao666666666 Summary: 量化筛选A股潜力股，结合资金流、技术指标、趋势强度、基本面和筹码集中度，提供多角度投资建议与风险提示。 Tags: latest:1.0.0 Version history: v1.0.0 | 2026-04-21T14:44:26.878Z | auto A股量化选股系统首发版本，全面支持多维度量化股票筛选。 - 三角色辩论式分析流程，提升选股决策严谨性 - 五大核心筛选维度：资金流向、量价技术、趋势强度、基本面、筹码集中 - 明确输出格式，支持标准股票卡片和梯队推荐列表 - 强化风险控制：持仓比例、止损线、高位禁买等规则 - 集成主流行情及资金流数据源，兼顾实时性和权威性 Archive index: Archive v1.0.0: 4 files, 4478 bytes Files:

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View on ClawHub Homepage

Rank

Safety

Downloads

1.4k

Updated

Oct 10, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.4K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.4K downloadsadoption · observed Oct 10, 2026
Latest release: 1.0.0release · observed Apr 21, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s1765qeddzdkjnngv8ydc0pb71840b53:a-stock-quantitative-screener

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-xiaobao666666666-a-stock-quantitative-screener/snapshot"

Documentation

CLAWHUB

5,375 characters of source documentation, loaded on request.

Extracted files

4 files captured from the source.

SKILL.md

# A股量化交易股票筛选系统

## 触发条件
当用户发送以下指令时触发：
- "帮我筛选A股量化股票"
- "分析A股量化交易机会"
- "量化选股"
- "筛选可能拉升的股票"
- "识别主力资金介入"
- "分析量化信号"

## 工作流程

本技能采用**三角色辩论式分析**流程：

```
角色1（筛选） → 角色2（反驳） → 角色3（综判） → 最终推荐
```

## 阶段一：A股量化特点分析

1. **成交活跃度高** - 日均成交额约1-2万亿
2. **散户占比高** - 超额机会多
3. **政策影响显著** - 监管政策影响大
4. **波动性大** - 趋势跟踪策略有效
5. **小盘股溢价** - 流动性溢价明显
6. **板块轮动快** - 行业轮动策略适用
7. **技术指标有效** - 量价数据被广泛使用
8. **北向资金影响** - 外资定价权逐渐增强

## 阶段二：五维筛选标准

### 1. 资金流向维度（权重30%）
- 主力资金连续净流入 ≥ 3日
- 超大单净流入占比 > 5%
- 北向资金持股比例上升
- 融资融券余额变化

### 2. 量价技术维度（权重25%）
- 成交量较20日均量放大 ≥ 1.5倍
- 5日均线上穿20日均线（金叉）
- 股价站上BOLL中轨
- MACD零轴上方金叉

### 3. 趋势强度维度（权重20%）
- 区间涨幅 5%-25%
- 相对大盘超额收益 > 3%
- 股价创20日新高
- 多周期均线多头排列

### 4. 基本面维度（权重15%）
- 市值：主板50-500亿
- PE：0-50倍
- 近两年净利润正增长
- 近一年无重大违规

### 5. 筹码集中度（权重10%）
- 股东户数连续减少
- 户均持股数增加
- 筹码趋向集中

## 阶段三：三角色分析

### 角色1：量化研究员（筛选）
1. 分析A股量化特点
2. 结合当日最新市场行情
3. 应用筛选标准识别量化资金介入信号
4. 输出符合条件的前10只股票
5. 附具体代码、名称、入选理由、风险提示

### 角色2：量化研究员（反驳）
验证角色1结果的合理性：
1. **技术指标有效性** - 质疑滞后性、参数敏感性
2. **资金流向可靠性** - 质疑数据划分标准
3. **基本面矛盾** - 质疑流动性陷阱
4. **样本偏差** - 质疑幸存者偏差
5. **执行问题** - 质疑滑点、延迟、风控缺失

### 角色3：量化研究员（综判）
综合评估双方观点：
1. 评估辩论双方的论据强度
2. 调整优化筛选标准
3. 更新最终股票池
4. 提供优先级排序
5. 给出具体投资建议

## 阶段四：风险控制

- 单只股票仓位 ≤ 10%
- 设置8%止损线
- 持仓不超过20只
- 避免高位追涨

## 输出格式

### 标准股票卡片
```
| 排名 | 代码 | 名称 | 入选理由 | 风险等级 |
|------|------|------|----------|----------|
| 1 | 600519 | 贵州茅台 | ①北向资金持续净买入②... | ⚠️ 中 |
```

### 最终推荐
```
第一梯队（确定性较高）：
1. 比亚迪（002594）
2. 招商银行（600036）

第二梯队（弹性较大）：
3. 中国平安（601318）
4. 恒瑞医药（600276）
```

## 数据来源
- thsdk：实时行情、K线、资金流
- stockapi：龙虎榜、游资席位
- 问财：板块、资金排名

## 注意事项
- 量化策略存在失效风险
- 技术指标具有滞后性
- 资金流向数据可能存在误差
- 市场环境变化影响策略有效性

_meta.json

{
  "ownerId": "kn716n9f5sv0gxjyn5gq6nt7n982cfa9",
  "slug": "a-stock-quantitative-screener",
  "version": "1.0.0",
  "publishedAt": 1776782666878
}

QUANT_DETAIL.md

# A股量化筛选标准详细说明

## 一、资金流向维度（权重30%）

### 主力资金判定
- 单笔成交>100万为主力资金
- 主力净流入 = 超大单净流入 + 大单净流入

### 北向资金
- 持股数量/比例/市值变化

### 融资融券
- 融资买入=做多情绪，融券卖出=做空情绪

## 二、量价技术维度（权重25%）

### 均线金叉/死叉
- 5日均线>20日均线 → 买入信号
- 5日均线<20日均线 → 卖出信号

### MACD
- 参数：12/26/9日
- MACD柱由负转正+DIFF上穿DEA → 买入

### BOLL布林带
- 中轨：20日均线；上轨：中轨+2倍标准差
- 股价突破中轨+成交量放大 → 买入

### KDJ
- K、D、J值<20 → 超卖 → 买入机会
- K、D、J值>80 → 超买 → 卖出风险

## 三、趋势强度（权重20%）

### RSI
- RSI<30 → 超卖 → 买入机会
- RSI>70 → 超买 → 卖出风险

### 超额收益
- 超额收益 = 个股收益率 - 沪深300收益率

## 四、基本面（权重15%）

### 市值筛选
- 主板50-500亿，兼顾流动性和弹性

### 估值
- PE历史分位数<30%为低估，>70%为高估

## 五、筹码集中度（权重10%）

- 股东户数减少 → 筹码集中
- 户均持股数增加 → 主力吸筹

## 六、综合评分

```
总分 = 资金流向×0.30 + 量价技术×0.25 + 趋势强度×0.20 + 基本面×0.15 + 筹码×0.10
```

- ≥70分 → 重点关注
- 60-70分 → 观察标的
- <60分 → 暂不推荐

## 七、风控

- 止损：买入价×0.92（8%止损）
- 单票仓位≤10%
- 持仓上限20只
- 行业集中度≤30%

skill-card.md

## Description:

Screens A-share stock opportunities using fund-flow, price-volume, trend-strength, fundamental, and shareholding-concentration signals, then provides ranked analysis with risk notes.

This skill is ready for commercial/non-commercial use.

## Publisher:

[xiaobao666666666](https://clawhub.ai/user/xiaobao666666666)

### License/Terms of Use:

MIT-0

## Use Case:

External users and analysts use this skill to ask an agent for structured A-share stock screening, debate-style review, tiered recommendations, and risk-control guidance. Outputs should be treated as informational market analysis, not as standalone trading advice.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Market data may be stale or incomplete, which can make screening results unreliable.

Mitigation: Verify current prices, fund-flow data, and corporate information against independent market data sources before acting.

Risk: The skill may produce stock rankings or investment suggestions that users could mistake for financial advice.

Mitigation: Treat outputs as educational analysis and combine them with independent research, suitability review, and professional judgment.

Risk: Quantitative indicators and technical signals can fail when market conditions change.

Mitigation: Apply position limits, stop-loss rules, diversification, and ongoing human review before making trading decisions.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/xiaobao666666666/skills/a-stock-quantitative-screener)

## Skill Output:

**Output Type(s):** [text, markdown, guidance]

**Output Format:** [Markdown tables and ranked recommendation lists with explanatory text]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Includes screening rationale, debate-style critique, prioritized stock lists, and risk-control notes.]

## Skill Version(s):

1.0.0 (source: server release metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

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