Predictive Modeling for Asset Bubble Detection in Financial Markets

Author(s)	Arpit Goyal, Pranay Goenka
Country	India
Abstract	This paper presents a comprehensive approach to predicting and detecting asset bubbles in financial markets, utilizing advanced analytics, machine learning models, and deep learning techniques. The study focuses on the S&P 500 as a representative indicator of the U.S. stock market, aiming to develop a robust methodology for identifying early signs of asset bubbles and providing actionable insights for investors, financial institutions, and policymakers.
Keywords	Market dynamics, GDP development
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 2, March-April 2024
Published On	2024-04-11
Cite This	Predictive Modeling for Asset Bubble Detection in Financial Markets - Arpit Goyal, Pranay Goenka - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.16959
DOI	https://doi.org/10.36948/ijfmr.2024.v06i02.16959
Short DOI	https://doi.org/gtqxtg

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		+91-9898-5948-55	editor@ijfmr.com

International Journal For Multidisciplinary Research