Dear all,
I am an early-stage user of the API environment, please excuse me for apparently redundant questions.
My aim is to gather management pay-related news from the last 365 days for every company in my portfolio (fewer than 550 RICs) at each fiscal year-end over the past 20 years, and perform sentiment analysis on each of them.
By reading the articles linked below, I have gathered part of what I need. However, I have some doubts related to the following:
- Is this something that can be done, or are there limits? Consider that, when using the NEWS app, the MPAY news are not so many (per company, per year);
- What’s the difference between using
ek.get_news_headlines and rd.news.get_headlines? They seem to work in the same way (i.e., as shown in the figure in link 2), but I do not fully understand the actual differences; - Both links mention that portfolios can be used. However, due to my very basic knowledge of script structure, I did not understand how to implement this;
- Both links specify that the time range can go up to 15 months. My doubt is: does this 15 months start from today (i.e., the last news that can be gathered was issued January 1st 2024) or from 15 months before the specified start date? When specifying an "old date" (e.g., 31-Dec-2022) in the script, I do not get any news for any company although in the NEWS app there are news on the topic: MPAY. Is this related to part of my service subscription, or is it a function issue?
- Both links describe performing sentiment analysis, but I did not understand (at least on the 2nd link) whether it is done on the headline of the news or the full text. Apparently, it is performed on the headline field. Am I correct? Was that only for demonstration purposes? Would it be feasible to perform sentiment analysis on a longer and more complex text?
My script now is this:
from datetime import datetime, timedelta
import pandas as pd
import rd
start = datetime(2024, 12, 31).date()
end = start - timedelta(days=365)
compNews = pd.DataFrame()
riclist = ['MSFT.O'.'AAPL.O']
for ric in riclist:
try:
cHeadlines = rd.news.get_headlines("R:" + ric + ' AND Language:LEN AND Topic:MPAY',
start=str(start),
end=str(end),
count=100)
cHeadlines['cRIC'] = ric
if not compNews.empty:
compNews = pd.concat([compNews, cHeadlines], ignore_index=True)
else:
compNews = cHeadlines
except Exception as e:
print(f"An error occurred with RIC {ric}: {e}")
compNews
Thank you for your time,
B
https://developers.lseg.com/en/article-catalog/article/introduction-news-sentiment-analysis-eikon-data-apis-python-example
https://developers.lseg.com/en/article-catalog/article/ai-driven-stock-insights--analyzing-financial-news-with-llms
