Fundamentals

Daily valuation and liquidity metrics, one row per stock per trading day, covering PE (trailing and TTM), PB, PS, dividend yield, turnover rate, volume ratio, share counts (total, float, free-float), and market caps (total and float). It updates alongside each day's close and suits valuation screening, cross-sectional ranking, size bucketing, and factor construction. Note that valuation ratios may be null or negative for loss-making firms, market caps are denominated in 10k CNY, and you should be explicit about which basis (TTM vs. static, float vs. total) you use.

GET /v2/market/fundamentals

Parameters

Name Type Required Description

symbol string No Stock code, e.g. 000001.SZ

start_date string No Start date (YYYYMMDD)

end_date string No End date (YYYYMMDD)

trade_date string No Trading date YYYYMMDD (single day)

Key Response Fields

Field Description

pe / pe_ttm Price-to-Earnings ratio (static / trailing 12m)

pb Price-to-Book ratio

ps / ps_ttm Price-to-Sales ratio

turnover_rate / turnover_rate_f Turnover rate (total / free float)

total_mv / circ_mv Total / circulating market cap (CNY 10k)

volume_ratio Volume ratio

API Example

cURL

curl -H "X-API-Key: YOUR_KEY" \
  "https://asharehub.com/v2/market/fundamentals?symbol=000001.SZ"

Python SDK

from asharehub import AShareHub

client = AShareHub(api_key="YOUR_KEY")
df = client.fundamentals(symbol="000001.SZ")
print(df.head())

Sample Data

returns a pandas.DataFrame

symbol	trade_date	close	turnover_rate	turnover_rate_f	volume_ratio	pe	pe_ttm	pb	ps	… +8
000001.SZ	20260626	10.23	0.6372	1.5152	1.01	4.6565	4.6104	0.4278	1.5103	…
000001.SZ	20260625	10.42	0.5586	1.3284	0.91	4.743	4.696	0.4357	1.5384	…
000001.SZ	20260624	10.51	0.5802	1.3796	0.97	4.784	4.7366	0.4395	1.5517	…

Query historical PE and PE TTM by date range

To retrieve historical price-to-earnings ratios for a Chinese A-share stock, pass symbol, start_date, and end_date to the fundamentals API. This example requests available records for June 2026 and sorts them by trading date. Use YYYYMMDD dates.

Python SDK

from asharehub import AShareHub

with AShareHub(api_key="YOUR_KEY") as client:
    history = client.fundamentals(
        symbol="000001.SZ",
        start_date="20260601",
        end_date="20260630",
    )

if history.empty:
    print("No valuation records for this symbol and date range.")
else:
    history = history.sort_values("trade_date")
    columns = ["symbol", "trade_date", "pe", "pe_ttm", "pb"]
    print(history[columns].to_string(index=False))

pe is the static PE ratio; pe_ttm uses trailing 12-month earnings. Keep these as separate series. Valuation ratios have no currency unit. Preserve missing values instead of filling them with zero, and do not automatically discard negative values. Responses contain available trading-day records, not a row for every calendar day.

Historical dates do not establish a point-in-time snapshot of what was known when financial statements were released. Check disclosure timing and revisions before using the series in a backtest. See Python SDK installation for setup and daily prices for the corresponding price series.