Adjustment Factor

Daily adjustment factors, one row per stock per trading day, used to convert unadjusted quotes into forward- or backward-adjusted prices. This endpoint returns raw factors and does not choose the forward-adjustment anchor for the caller.

GET /v2/market/adj-factor

Formulas and anchor

Let P(t) be the unadjusted price and F(t) the factor on date t. Choose anchor trading date T as the last trading day on or before the target end_date; when omitted, use the latest available trading day.

Unadjusted price = P(t)
Forward-adjusted price = P(t) × F(t) / F(T)
Backward-adjusted price = P(t) × F(t)

Forward adjustment guarantees adjusted_price(T) = P(T). The same historical date can have a different absolute forward-adjusted price under a different anchor. Apply these formulas to open, high, low, and close, not to volume or turnover. Recompute cached forward-adjusted series after a corporate action or factor revision.

The *_qfq fields from technical-factors are snapshots using the latest anchor available at the source's last refresh. For a historical anchor or strict reproducibility, calculate from unadjusted daily prices and this endpoint's factors.

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)

Response Fields

Field Type Description

symbol string Stock code

trade_date string Trading date

adj_factor number Adjustment factor

API Example

cURL

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

Python SDK

from asharehub import AShareHub

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

Sample Data

returns a pandas.DataFrame

symbol	trade_date	adj_factor
000001.SZ	20260626	139.008
000001.SZ	20260625	139.008
000001.SZ	20260624	139.008