ricequant/ricequant-skills/earnings-analysis

earnings-analysis/
├── SKILL.md
├── scripts/
│   ├── extract_announcements.py
│   └── generate_report.py
├── assets/
│   └── template.md
└── references/
    ├── data_contract.md
    └── web_search.md

REPORT_DATE="${REPORT_DATE:-2026-04-07}"
ORDER_BOOK_ID="${ORDER_BOOK_ID:-600519.XSHG}"
PRICE_WINDOW_START="$(python3 - <<PY
from datetime import date, timedelta
report_date = date.fromisoformat("${REPORT_DATE}")
print((report_date - timedelta(days=45)).isoformat())
PY
)"
CONSENSUS_START="$(python3 - <<PY
from datetime import date, timedelta
report_date = date.fromisoformat("${REPORT_DATE}")
print((report_date - timedelta(days=90)).isoformat())
PY
)"
FACTOR_DATE="$(python3 - <<PY
import json
import subprocess
from datetime import date, timedelta
 
def has_non_empty_factor(day: str) -> bool:
    payload = json.dumps({
        "order_book_ids": ["${ORDER_BOOK_ID}"],
        "factor": "market_cap",
        "start_date": day,
        "end_date": day,
    }, ensure_ascii=False)
    rows = json.loads(subprocess.check_output(
        ["rqdata", "stock", "cn", "financial-indicator", "--payload", payload, "--format", "json"],
        text=True,
    ))
    return any(isinstance(row, dict) and row.get("market_cap") not in (None, "", "null") for row in rows)
 
cursor = date.fromisoformat("${REPORT_DATE}")
for _ in range(15):
    if has_non_empty_factor(cursor.isoformat()):
        print(cursor.isoformat())
        break
    cursor -= timedelta(days=1)
else:
    raise SystemExit("最近 15 个自然日都未找到非空 market_cap 因子日期")
PY
)"
HISTORY_START_QUARTER="$(python3 - <<PY
from datetime import date
report_date = date.fromisoformat("${REPORT_DATE}")
print(f"{report_date.year - 2}q1")
PY
)"
HISTORY_END_QUARTER="$(python3 - <<PY
from datetime import date
report_date = date.fromisoformat("${REPORT_DATE}")
print(f"{report_date.year}q4")
PY
)"
 
DATA_DIR="${DATA_DIR:-$HOME/rq_equities_reports/earnings_analysis}"
OUTPUT_MD="${OUTPUT_MD:-$DATA_DIR/earnings_analysis_${ORDER_BOOK_ID}_${REPORT_DATE}.md}"

mkdir -p "$DATA_DIR"
 
rqdata stock cn instruments --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"]
}" --format json > "$DATA_DIR/company_info.json"
 
rqdata stock cn industry --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"date\": \"$REPORT_DATE\",
  \"level\": 0,
  \"source\": \"citics_2019\"
}" --format json > "$DATA_DIR/industry.json"
 
rqdata stock cn financial --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"fields\": [\"revenue\", \"net_profit\", \"gross_profit\", \"cash_from_operating_activities\", \"total_assets\", \"total_liabilities\"],
  \"start_quarter\": \"$HISTORY_START_QUARTER\",
  \"end_quarter\": \"$HISTORY_END_QUARTER\",
  \"statements\": \"all\"
}" --format json > "$DATA_DIR/historical_financials.json"
 
rqdata stock cn financial-indicator --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"factor\": \"return_on_equity_weighted_average\",
  \"start_date\": \"$CONSENSUS_START\",
  \"end_date\": \"$FACTOR_DATE\"
}" --format json > "$DATA_DIR/roe_history.json"
 
rqdata stock cn financial-indicator --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"factor\": \"market_cap\",
  \"start_date\": \"$FACTOR_DATE\",
  \"end_date\": \"$FACTOR_DATE\"
}" --format json > "$DATA_DIR/market_cap.json"
 
rqdata stock cn financial-indicator --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"factor\": \"pe_ratio\",
  \"start_date\": \"$FACTOR_DATE\",
  \"end_date\": \"$FACTOR_DATE\"
}" --format json > "$DATA_DIR/pe_ratio.json"
 
rqdata stock cn financial-indicator --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"factor\": \"pb_ratio\",
  \"start_date\": \"$FACTOR_DATE\",
  \"end_date\": \"$FACTOR_DATE\"
}" --format json > "$DATA_DIR/pb_ratio.json"
 
rqdata stock cn financial-indicator --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"factor\": \"dividend_yield\",
  \"start_date\": \"$FACTOR_DATE\",
  \"end_date\": \"$FACTOR_DATE\"
}" --format json > "$DATA_DIR/dividend_yield.json"
 
rqdata stock cn price --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"start_date\": \"$PRICE_WINDOW_START\",
  \"end_date\": \"$REPORT_DATE\",
  \"fields\": [\"close\", \"volume\", \"total_turnover\"],
  \"adjust_type\": \"post\"
}" --format json > "$DATA_DIR/price_window.json"
 
rqdata index price --payload "{
  \"order_book_ids\": [\"000300.XSHG\"],
  \"start_date\": \"$PRICE_WINDOW_START\",
  \"end_date\": \"$REPORT_DATE\",
  \"fields\": [\"close\"]
}" --format json > "$DATA_DIR/benchmark_window.json"

rqdata stock cn consensus --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"start_date\": \"$CONSENSUS_START\",
  \"end_date\": \"$REPORT_DATE\",
  \"report_range\": 3
}" --format json > "$DATA_DIR/consensus.json"
 
TARGET_FISCAL_YEAR="$(python3 - "$DATA_DIR/historical_financials.json" "$REPORT_DATE" <<'PY'
import json
import sys
from datetime import date, datetime
from pathlib import Path
 
def parse_iso_date(value):
    if not value:
        return None
    for fmt in ("%Y-%m-%d", "%Y-%m-%d %H:%M:%S"):
        try:
            return datetime.strptime(str(value)[:19], fmt).date()
        except ValueError:
            continue
    return None
 
rows = json.loads(Path(sys.argv[1]).read_text())
report_date = date.fromisoformat(sys.argv[2])
best = None
for row in rows:
    info_date = parse_iso_date(row.get("info_date"))
    quarter = row.get("quarter")
    if not info_date or info_date > report_date or not quarter:
        continue
    if best is None or quarter > best:
        best = quarter
print(best[:4] if best else report_date.year)
PY
)"
 
rqdata stock cn research-reports --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"fiscal_year\": \"$TARGET_FISCAL_YEAR\",
  \"start_date\": \"$CONSENSUS_START\",
  \"end_date\": \"$REPORT_DATE\",
  \"date_rule\": \"create_tm\"
}" --format json > "$DATA_DIR/research_reports.json"
 
ANNOUNCEMENT_START="$(python3 - <<PY
from datetime import date, timedelta
report_date = date.fromisoformat("${REPORT_DATE}")
print((report_date - timedelta(days=45)).isoformat())
PY
)"
 
rqdata stock cn announcement --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"start_date\": \"$ANNOUNCEMENT_START\",
  \"end_date\": \"$REPORT_DATE\"
}" --format json > "$DATA_DIR/announcement_raw.json"

python3 earnings-analysis/scripts/extract_announcements.py \
  --stock "$ORDER_BOOK_ID" \
  --data-dir "$DATA_DIR" \
  --report-date "$REPORT_DATE"

python3 earnings-analysis/scripts/generate_report.py \
  --stock "$ORDER_BOOK_ID" \
  --data-dir "$DATA_DIR" \
  --report-date "$REPORT_DATE" \
  --output "$OUTPUT_MD"