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How to do fund performance analysis using Refinitiv.Data?

I'm a student doing my master's thesis and I've been instructed by my former supervisor to use Refinitiv dataplatform so seek data and do calculations needed for the thesis in Python.


I've been trying to figure things out with documentation and tutorials for weeks and I'm unable to proceed. Also I'm not able to get any help from the school as my current supervisor doesn't know how to use the program.

I'm able to get historical closing prices of the needed active ETFs but I'm unable to proceed with calculations in Python. Any help or push to right direction would be greatly appreciated.

Example of the code from one Active ETF:

import refinitiv.data as rd
from refinitiv.data.content import historical_pricing
from refinitiv.data.content.historical_pricing import Intervals
from refinitiv.data.content.historical_pricing import Adjustments
from refinitiv.data.content.historical_pricing import MarketSession
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import asyncio
import datetime

rd.open_session()

response = historical_pricing.summaries.Definition(
    universe = "JEPI.K",
    interval = historical_pricing.Intervals.DAILY,
    start = datetime.date(2020, 1, 1), 
    end = datetime.date(2020, 12, 31),
    fields = ["TRDPRC_1"],
    adjustments = [
        Adjustments.EXCHANGE_CORRECTION,
        Adjustments.MANUAL_CORRECTION
    ]
).get_data()
# Extract in DataFrame format

response.data.df


JEPI.K TRDPRC_1
Date
2020-05-21 49.9345
2020-05-22 50.0935
2020-05-26 50.2383
2020-05-27 50.6274
2020-05-28 51.14
.........
2020-12-24 55.6026
2020-12-28 55.87
2020-12-29 55.91
2020-12-30 55.35
2020-12-31 55.75
156 rows × 1 columns
#technologyrefinitiv-data-platformdata
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Hi @Ville L, I have liaised with our internal teams to try and find a solution for your inquiry. I will revert to you on this Forum as soon as I have an update.

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@Ville L Thanks for your question - funds have the concept of total return which includes dividends - this is how typically they are analysed - see my code below:

import refinitiv.data as rd
rd.open_session()
df = rd.get_history(['JEPI.K','PSFD.K','SPUC.K'],['TR.TotalReturn.date','TR.TotalReturn'],start='2023-08-01',end ='2024-03-04',interval = '1D')
df

1709650538350.png

This is providing you with daily returns series for whatever period and can then be cumulatively summed etc. To get a universe of fund peers app (type FPEERS into Eikon Search bar). I hope this can help.


1709650538350.png (179.6 KiB)
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