Discrepancies/Errors between Python API and Refinitiv Eikon data
Hello,
I have been recently retrieving brokerage recommendations from Reuters using the Python Eikon API.
I am interested in the price target and the grade recommendation assigned by a brokerage to a stock.
Because I need this information to be accurate, I have been handchecking data returned and have found many
errors and discrepancies between what the Python API returns and what is shown by Eikon in the Reuters terminal.
For example, I use the following code to pull recommendations for ticker IRT:
import json
symbol_list = ['IRT']
fields = [
'TR.TPEstvalue.brokername',
'TR.TPEstValue', 'TR.TPEstValue.date',
'TR.BrkRecLabel', 'TR.TPEstvalue.analystname',
'TR.RecLabelEst',
'TR.RecEstValue', 'TR.BrkRecEstConfirmDate'
]
data = ek.get_data(instruments=symbol_list, fields=fields, raw_output=True)
print(json.dumps(data, indent=2, sort_keys=True))
The results for brokerage RBC are the following:
Python API says RBC is at a Neutral rating for ticker IRT.
However, the following is returned for when looking at recommendations on the Reuters Terminal:
As you can notice, the true grade is an Outperform/Buy rating, not Neutral.
I have posted before on this issue (see "Possible BrkRecLabel and RecEstValue Data Errors"), and this is not an issue of fields retrieved.
I have also been in contact with the Eikon Help Desk, who confirmed data is correct on their end (see case 11302953).
This is a Python API data issue that needs to be corrected. Let me know if more examples would be helpful. These discrepancies appear
in many brokerages and stocks so I have many available.
Best Answer
-
Hi @bshapiro
I've reached out to content specialist who provided an explanation as to what is happening. Specifically, it appears to be a common issue if you mix specific data sets - target price and broker recommendations - in one request. Each data set is sorted differently in the backend.
A proposed solution is to perform 2 separate queries for the different datasets and combine them.
For example:
import eikon as ek
import pandas as pd
from functools import reduce
...
symbol_list = ['IRT']
fields = ['TR.BrkRecLabel.brokername', 'TR.BrkRecLabel',
'TR.BrkRecLabel.date'
]
data1, err = ek.get_data(instruments=symbol_list, fields=fields)
data1symbol_list = ['IRT']
fields = ['TR.TPEstValue.brokername', 'TR.TPEstValue.analystname',
'TR.TPEstValue', 'TR.TPEstValue.date'
]
data2, err = ek.get_data(instruments=symbol_list, fields=fields)
data2Combine them:
result = reduce(lambda x,y: pd.merge(x,y, on='Broker Name', how='outer'), [data1, data2])
result1
Answers
-
I can confirm Refinitiv Eikon data is correct since I have the most recent RBC publishing that declares the recommendation:
0 -
Hi @bshapiro,
I've reached out to the content specialist team to get involved. Sorry for the long delay - I will keep a close watch on this and ensure someone will get back to you.
0
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