How to get last closing day prices

himanshu19

Hi Team

We are using PriceHistoryExtractionRequest to fetch prices for a date range

In one of case, QueryStartDate was an exchange holiday so api didn't return any price.

Is there any flag we can set in API, so that API can return last closing day price in case QueryStartDate/QueryEndDate is an exchange holiday.

Kind Regards

Jirapongse Phuriphanvichai

@himanshu19

Thank you for reaching out to us.

The question appears to be similar to the LSEG DSS API - Price History discussion.

I checked the parameters in the API Reference Tree but could not find any that can be used to retrieve the last available closing price. However, please contact the Datascope Select support team directly via LSEG Support to confirm this.

You can programmatically fill in the missing dates (holidays). The following is the sample Python code.

import requests
import json
import pandas as pd

token = '<DSS Token>'
url = "https://selectapi.datascope.lseg.com/RestApi/v1/Extractions/ExtractWithNotes"

payload = json.dumps({
  "ExtractionRequest": {
    "@odata.type": "#DataScope.Select.Api.Extractions.ExtractionRequests.PriceHistoryExtractionRequest",
    "ContentFieldNames": [
      "File Code",
      "RIC",
      "Trade Date",
      "Last Trade Price",
      "Universal Close Price",
      "Alternate Close Price",
      "High Price",
      "Low Price",
      "Open Price",
      "Volume Weighted Average Price",
      "Turnover",
      "Volume",
      "Accumulated Volume Unscaled",
      "Bid Price",
      "Asset Type",
      "Quote ID",
      "Bid Yield",
      "Exchange Code",
      "Currency Code"
    ],
    "IdentifierList": {
      "@odata.type": "#DataScope.Select.Api.Extractions.ExtractionRequests.InstrumentIdentifierList",
      "InstrumentIdentifiers": [
        {
          "Identifier": "PTT.BK",
          "IdentifierType": "Ric"
        }
      ],
      "ValidationOptions": {
        "AllowHistoricalInstruments": True
      },
      "UseUserPreferencesForValidationOptions": False
    },
    "Condition": {
      "AdjustedPrices": True,
      "QueryStartDate": "2026-07-01T00:00:00.000Z",
      "QueryEndDate": "2026-07-31T00:00:00.000Z",
      "LastEntityOnly": True
    }
  }
})
headers = {
  'Prefer': 'respond-async',
  'Content-Type': 'application/json',
  'Authorization': 'Token '+token
}

response = requests.request("POST", url, headers=headers, data=payload)

data = response.json()
//Convert data to a data frame
df = pd.DataFrame(data['Contents'])

//Set 'Trade Data' as as index
df = df.set_index('Trade Date')

//fill in missing dates with the preivous data
df.index = pd.to_datetime(df.index)
df = df.resample('D').ffill()
df