ricequant/ricequant-skills/initiating-coverage

initiating-coverage/
├── SKILL.md
├── scripts/
│   └── generate_report.py
├── assets/
│   └── template.md
└── references/
    ├── data_contract.md
    └── web_search.md

REPORT_DATE="${REPORT_DATE:-$(date +%F)}"
ORDER_BOOK_ID="${ORDER_BOOK_ID:-600519.XSHG}"
BENCHMARK_ORDER_BOOK_ID="${BENCHMARK_ORDER_BOOK_ID:-000300.XSHG}"
PRICE_START_DATE="$(python3 - <<PY
from datetime import date, timedelta
report_date = date.fromisoformat("${REPORT_DATE}")
print((report_date - timedelta(days=365 * 3 + 30)).isoformat())
PY
)"
CONSENSUS_START_DATE="$(python3 - <<PY
from datetime import date, timedelta
report_date = date.fromisoformat("${REPORT_DATE}")
print((report_date - timedelta(days=210)).isoformat())
PY
)"
HISTORY_START_QUARTER="$(python3 - <<PY
from datetime import date
report_date = date.fromisoformat("${REPORT_DATE}")
print(f"{report_date.year - 5}q1")
PY
)"
HISTORY_END_QUARTER="$(python3 - <<PY
from datetime import date
report_date = date.fromisoformat("${REPORT_DATE}")
print(f"{report_date.year}q4")
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
)"
 
DATA_DIR="${DATA_DIR:-$HOME/rq_equities_reports/initiating_coverage}"
OUTPUT_MD="${OUTPUT_MD:-$DATA_DIR/initiating_coverage_${ORDER_BOOK_ID}_${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 shares --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"start_date\": \"$CONSENSUS_START_DATE\",
  \"end_date\": \"$REPORT_DATE\"
}" --format json > "$DATA_DIR/shares.json"
 
rqdata stock cn shareholder-top10 --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"start_date\": \"$CONSENSUS_START_DATE\",
  \"end_date\": \"$REPORT_DATE\",
  \"start_rank\": 1,
  \"end_rank\": 10
}" --format json > "$DATA_DIR/shareholder_top10.json"
 
rqdata stock cn financial --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"fields\": [
    \"revenue\",
    \"net_profit\",
    \"gross_profit\",
    \"total_assets\",
    \"total_liabilities\",
    \"total_equity\",
    \"cash_from_operating_activities\",
    \"cash_flow_from_investing_activities\",
    \"cash_flow_from_financing_activities\"
  ],
  \"start_quarter\": \"$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\": [\"$ORDER_BOOK_ID\"],
  \"factor\": \"return_on_equity_weighted_average\",
  \"start_date\": \"$PRICE_START_DATE\",
  \"end_date\": \"$FACTOR_DATE\"
}" --format json > "$DATA_DIR/roe_history.json"
 
for factor in market_cap pe_ratio pb_ratio dividend_yield; do
  rqdata stock cn financial-indicator --payload "{
    \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
    \"factor\": \"$factor\",
    \"start_date\": \"$FACTOR_DATE\",
    \"end_date\": \"$FACTOR_DATE\"
  }" --format json > "$DATA_DIR/${factor}.json"
done
 
rqdata stock cn price --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"start_date\": \"$PRICE_START_DATE\",
  \"end_date\": \"$REPORT_DATE\",
  \"fields\": [\"close\", \"volume\", \"total_turnover\", \"high\", \"low\"],
  \"adjust_type\": \"post\"
}" --format json > "$DATA_DIR/price_history.json"
 
rqdata stock cn turnover-rate --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"start_date\": \"$PRICE_START_DATE\",
  \"end_date\": \"$REPORT_DATE\"
}" --format json > "$DATA_DIR/turnover_history.json"
 
rqdata index price --payload "{
  \"order_book_ids\": [\"$BENCHMARK_ORDER_BOOK_ID\"],
  \"start_date\": \"$PRICE_START_DATE\",
  \"end_date\": \"$REPORT_DATE\",
  \"fields\": [\"close\"]
}" --format json > "$DATA_DIR/benchmark_price.json"
 
rqdata stock cn dividend --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"start_date\": \"$(python3 - <<PY
from datetime import date
report_date = date.fromisoformat("${REPORT_DATE}")
print(f\"{report_date.year - 5}-01-01\")
PY
)\",
  \"end_date\": \"$REPORT_DATE\"
}" --format json > "$DATA_DIR/dividend_history.json"
 
rqdata stock cn consensus --payload "{
  \"order_book_ids\": [\"$ORDER_BOOK_ID\"],
  \"start_date\": \"$CONSENSUS_START_DATE\",
  \"end_date\": \"$REPORT_DATE\",
  \"report_range\": 3
}" --format json > "$DATA_DIR/consensus.json"

read LATEST_QUARTER LATEST_YEAR NEXT_YEAR <<EOF
$(python3 - "$DATA_DIR/historical_financials.json" "$REPORT_DATE" <<'PY'
import json
import sys
from datetime import date
 
payload = json.load(open(sys.argv[1], "r", encoding="utf-8"))
report_date = date.fromisoformat(sys.argv[2])
 
records = payload if isinstance(payload, list) else payload.get("data", [])
best = None
for item in records:
    if not isinstance(item, dict):
        continue
    quarter = str(item.get("quarter") or "").lower()
    info_date = str(item.get("info_date") or "")[:10]
    if not quarter or not info_date:
        continue
    if info_date > report_date.isoformat():
        continue
    if best is None or quarter > best:
        best = quarter
 
if not best:
    raise SystemExit("未识别到最新财报季度")
year = int(best[:4])
print(best, year, year + 1)
PY
)
EOF
 
python3 - "$DATA_DIR" "$ORDER_BOOK_ID" "$LATEST_YEAR" "$NEXT_YEAR" "$CONSENSUS_START_DATE" "$REPORT_DATE" <<'PY'
import json
import subprocess
import sys
from pathlib import Path
 
data_dir = Path(sys.argv[1])
stock = sys.argv[2]
years = [sys.argv[3], sys.argv[4]]
start_date = sys.argv[5]
end_date = sys.argv[6]
 
rows = []
for year in years:
    payload = json.dumps({
        "order_book_ids": [stock],
        "fiscal_year": year,
        "start_date": start_date,
        "end_date": end_date,
        "date_rule": "create_tm",
    }, ensure_ascii=False)
    output = subprocess.check_output(
        ["rqdata", "stock", "cn", "research-reports", "--payload", payload, "--format", "json"],
        text=True,
    )
    data = json.loads(output)
    rows.extend(data if isinstance(data, list) else data.get("data", []))
 
data_dir.joinpath("research_reports.json").write_text(
    json.dumps(rows, ensure_ascii=False, indent=2),
    encoding="utf-8",
)
PY