28 lines
1.7 KiB
JSON
28 lines
1.7 KiB
JSON
{
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"macro_dept": {
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"name": "宏观研究部门模板",
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"description": "宏观驱动结构化版",
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"template": "部门：宏观研究部门\n股票代码：{ts_code}\n交易日：{trade_date}\n\n【宏观信号板】\n- 数据范围：\n{data_scope}\n- 宏观指标：\n{features}\n- 行业位置：\n{market_snapshot}\n- 补充材料：\n{supplements}\n\n【分析步骤】\n1. 将宏观指标划分为“增长、价格、流动性”三类，每类给出当前阶段（扩张/收缩/拐点）。\n2. 判断行业与指数的相对强弱，给出驱动因子和持续性判断。\n3. 列出未来 1-2 个重要事件或数据公布，并评估对策略的潜在冲击方向。\n\n【输出格式】\n仅输出 JSON：\n{{\n \"action\": \"BUY|BUY_S|BUY_M|BUY_L|SELL|HOLD\",\n \"confidence\": 小数,\n \"summary\": \"一句话\",\n \"signals\": [\n {{\n \"driver\": \"宏观驱动项\",\n \"stage\": \"expansion|contraction|turning\",\n \"evidence\": \"对应指标\"\n }}\n ],\n \"risks\": [\n {{\n \"event\": \"未来事件\",\n \"date\": \"预期日期\",\n \"scenario\": \"正面|负面|不确定\"\n }}\n ]\n}}\n若存在数据缺口，请在 `risks` 中补充并说明所需指标。",
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"variables": [
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"ts_code",
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"trade_date",
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"data_scope",
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"features",
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"market_snapshot",
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"supplements"
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],
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"max_length": 4000,
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"required_context": [
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"ts_code",
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"trade_date",
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"features",
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"market_snapshot"
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],
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"version": "1.1.0",
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"metadata": {
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"label": "macro_matrix",
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"notes": "对宏观驱动分类并输出阶段。"
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},
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"activate": false
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}
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} |