How to get data on companies that have been listed on the STOXX Europe 600 from 2015-2022?

Hi,

I want to identify those companies that have been listed on the STOXX Europe 600 during the whole period of 2015-2022, and exclude those that have joined or leaved during the period. Is there a simple way to do this?

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Accepted answers

jason.ramchandani01

@lauri.karimo Thanks for your question - here is how you can get a list of leavers and joiners using the Refinitiv Data Libraries:

import refinitiv.data as rd

rd.open_session()

rd.get_data(['.STOXX'], 
            ['TR.IndexJLConstituentChangeDate','TR.IndexJLConstituentRIC.change','TR.IndexJLConstituentRIC'],
            {'SDate':'-1Y', 'EDate':'-7Y', 'IC':'B'})

Is this what you are looking for? I hope this can help.

All comments

jason.ramchandani01

@lauri.karimo Thanks for your question - here is how you can get a list of leavers and joiners using the Refinitiv Data Libraries:

import refinitiv.data as rd

rd.open_session()

rd.get_data(['.STOXX'], 
            ['TR.IndexJLConstituentChangeDate','TR.IndexJLConstituentRIC.change','TR.IndexJLConstituentRIC'],
            {'SDate':'-1Y', 'EDate':'-7Y', 'IC':'B'})

Is this what you are looking for? I hope this can help.

jonathan.legrand

Hi @lauri.karimo ,

Using the Data Item Browser, I found the following

This gives you the Joiners, Leavers and Both. With this, you can filter out joiners within your time period:

import pandas as pd
# !pip install refinitiv-data
import refinitiv.data as rd  # pip install httpx==0.21.3 or 0.14.2
rd.open_session(
    name="desktop.workspace",
    config_name="C:/Example.DataLibrary.Python-main/Configuration/refinitiv-data.config.json")

df1: pd.DataFrame = rd.get_history(
    universe=["0#.STOXX50"],
    fields=['TR.ClosePrice'],
    start = '2022-01-31',
    end = '2023-01-30',
    interval="daily")

df2: pd.DataFrame = rd.get_data(
    universe=[".STOXX50"],
    fields=['TR.IndexJLConstituentChangeDate','TR.IndexJLConstituentName',
            'TR.IndexJLConstituentRIC','TR.IndexJLConstituentComName'],
    parameters={'IC':'J', 'SDate':'2022-01-31', 'EDate':'2023-01-30'})

RICs_to_inc: list = [i for i in df1.columns if i not in df2["Constituent RIC"].to_list()]

df: pd.DataFrame = df1[RICs_to_inc]

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