趋势定投之路

05-宏观周期查询

宏观经济指标查询，支撑中间段经济指标分析与周期判断。指标编码见 02-数据架构与表结构设计。

指标列表

SELECT DISTINCT indicator_code, indicator_name, unit, frequency, source
FROM macro_indicator
ORDER BY frequency, indicator_code;

单指标历史序列

from db import get_connection
from query_utils import query_to_df

conn = get_connection()
df = query_to_df(conn, """
    SELECT report_date, value, unit, source
    FROM macro_indicator
    WHERE indicator_code = ?
    ORDER BY report_date
""", ("CPI_YOY",))

绘制宏观指标曲线

import matplotlib.pyplot as plt

fig, ax = plt.subplots(figsize=(12, 4))
ax.plot(df["report_date"], df["value"], marker="o")
ax.axhline(0, color="gray", ls="--", alpha=0.5)
ax.axhline(3, color="red", ls="--", alpha=0.3, label="通胀警戒线 3%")
ax.set_title("CPI 同比")
ax.set_ylabel(df["unit"].iloc[0])
ax.legend()
plt.show()

多指标对比

CPI vs PPI（通胀传导）

SELECT
    c.report_date,
    c.value AS cpi_yoy,
    p.value AS ppi_yoy,
    c.value - p.value AS cpi_ppi_gap
FROM macro_indicator c
JOIN macro_indicator p
    ON c.report_date = p.report_date AND p.indicator_code = 'PPI_YOY'
WHERE c.indicator_code = 'CPI_YOY'
ORDER BY c.report_date DESC
LIMIT 24;

CPI - PPI 剪刀差扩大通常意味着下游盈利承压。

PMI 趋势

SELECT report_date, value
FROM macro_indicator
WHERE indicator_code = 'PMI_MANUFACTURING'
  AND report_date >= date('now', '-2 years')
ORDER BY report_date;

PMI > 50 为扩张，< 50 为收缩。连续 3 个月同方向变化通常预示趋势。

M2 与社融

SELECT
    m.report_date,
    m.value AS m2_yoy,
    s.value AS social_finance
FROM macro_indicator m
LEFT JOIN macro_indicator s
    ON m.report_date = s.report_date AND s.indicator_code = 'SOCIAL_FINANCE'
WHERE m.indicator_code = 'M2_YOY'
ORDER BY m.report_date DESC
LIMIT 24;

M2 增速反映货币宽松程度，社融反映实体融资需求。

利率环境

十年期国债收益率

SELECT report_date, value
FROM macro_indicator
WHERE indicator_code = 'TBOND_10Y'
ORDER BY report_date DESC
LIMIT 30;

十年期国债收益率是资产定价的锚：

  • 收益率下行：利好成长股、高估值资产
  • 收益率上行：利好价值股、银行保险等

LPR 变化

SELECT report_date, value
FROM macro_indicator
WHERE indicator_code = 'LPR_1Y'
ORDER BY report_date DESC
LIMIT 12;

LPR 下调通常伴随宽松周期，对股市整体偏利好。

周期阶段判断

综合多指标判断当前经济周期阶段：

SELECT
    (SELECT value FROM macro_indicator WHERE indicator_code = 'PMI_MANUFACTURING'
     ORDER BY report_date DESC LIMIT 1) AS pmi_latest,
    (SELECT value FROM macro_indicator WHERE indicator_code = 'PMI_MANUFACTURING'
     ORDER BY report_date DESC LIMIT 1 OFFSET 3) AS pmi_3m_ago,
    (SELECT value FROM macro_indicator WHERE indicator_code = 'CPI_YOY'
     ORDER BY report_date DESC LIMIT 1) AS cpi_latest,
    (SELECT value FROM macro_indicator WHERE indicator_code = 'PPI_YOY'
     ORDER BY report_date DESC LIMIT 1) AS ppi_latest,
    (SELECT value FROM macro_indicator WHERE indicator_code = 'M2_YOY'
     ORDER BY report_date DESC LIMIT 1) AS m2_latest,
    (SELECT value FROM macro_indicator WHERE indicator_code = 'TBOND_10Y'
     ORDER BY report_date DESC LIMIT 1) AS tbond_10y;

周期阶段粗判：

PMI 趋势CPI/PPIM2 增速周期阶段定投倾向
上升低位上升复苏积极定投
上升上升平稳过热谨慎，关注估值
下降上升下降滞胀防御，低估值优先
下降下降上升衰退定投优质宽基

宏观与指数交叉

估值分位 vs 利率环境

SELECT
    v.trade_date,
    v.index_code,
    d.index_name,
    v.pe_percentile,
    m.value AS tbond_10y
FROM index_valuation v
JOIN dim_index d ON v.index_code = d.index_code
LEFT JOIN macro_indicator m
    ON m.indicator_code = 'TBOND_10Y'
    AND m.report_date = v.trade_date
WHERE v.index_code = '000300'
  AND v.trade_date >= date('now', '-1 year')
  AND v.data_quality IN ('ok', 'manual_fixed')
ORDER BY v.trade_date;

低利率 + 低估值是定投黄金窗口，高利率 + 高估值需要谨慎。

封装函数建议

def get_macro_series(conn, indicator_code: str, years: int = 5) -> pd.DataFrame:
    """获取单指标历史序列。"""

def get_macro_snapshot(conn) -> dict:
    """获取所有指标最新值快照。"""

def get_macro_index_cross(conn, index_code: str,
                          macro_codes: list) -> pd.DataFrame:
    """获取指数估值与宏观指标的交叉表。"""