International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 2 (March-April 2026) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 2
March-April 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

How well does AI sentiment on ECB rate/QE news predict subsequent short-term Euronext 100 realized volatility?

Author(s) Mr. Dhairya Mittal, Mr. Ruhaan Mukherjee, Mr. Sadashiv Babbar, Mr. Ritvik Kunchakuri, Mr. Aditya Khemani
Country India
Abstract This paper investigates the predictive power of artificial intelligence (AI)-based
sentiment analysis on European Central Bank (ECB) monetary policy
communications—specifically rate decisions and quantitative easing (QE)
announcements—on the short-term realized volatility of the Euronext 100 Index.
Leveraging natural language processing (NLP) techniques, sentiment scores are
extracted from ECB press releases and news coverage. We then assess whether these
sentiment measures can serve as leading indicators for post-announcement market
volatility over one-day to five-day windows. Our empirical analysis utilizes
high-frequency Euronext 100 data and multiple regression models with control
variables, including macroeconomic indicators and lagged volatility. Results indicate a
statistically significant relationship between ECB sentiment and short-term realized
volatility, with dovish sentiment correlating with increased volatility under high
inflationary conditions. These findings offer practical applications for short-term risk
modeling and highlight the potential of AI in understanding how language influences
financial markets.
Keywords AI sentiment analysis, ECB, Euronext 100, quantitative easing, interest rates, NLP, volatility forecasting, realized volatility, monetary policy, financial markets
Field Sociology > Banking / Finance
Published In Volume 7, Issue 5, September-October 2025
Published On 2025-09-06
DOI https://doi.org/10.36948/ijfmr.2025.v07i05.52708
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 8 Isu 2Cover Page Vol 8 Isu 1Cover Page Vol 7 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com
Powered by Sky Research Publication and Journals