Volatility-Based Stock Categorization and Risk-Informed Investment Support System

Title

Volatility-Based Stock Categorization and Risk-Informed Investment Support System

Creator

Dinesh, J.; Suresh, K.; Cynthia, T.

Description

This paper presents an application that will benefit novice investors by categorizing stocks by levels of volatility so users can better understand risk by average parameters and increase factors assessed for long-term wealth generation. The offering model supports portfolio creation by enabling novice investors to choose appropriate options based on their risk tolerance, something that would be more challenging for investors with limited financial savvy under different circumstances. To develop an investment companion application that reduces emotional investing and increases strategic long-term financial decision making through effective data visualization, especially for novices. An application that uses statistics on volatility to compartmentalize stocks by low, medium and high-risk options for selection, with the ability to create and assess a portfolio based on this criteria through a virtual interface. Increased investment construction accessibility, the ability to create diverse portfolios, and a foundation for subsequent advanced investment features like notifications and trend predictive analysis. 2026 IEEE.

Source

2026 2nd International Conference on Cognitive Computing in Engineering, Communications, Sciences and Biomedical Health Informatics, IC3ECSBHI 2026;pp.847-852

Date

01-01-2026

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Financial technology; Investor support; Portfolio management; Risk management; Stock categorization strategy; Stock volatility; Volatility index

Coverage

Dinesh J., Christ University, Computer Science Department, Bangalore, India; Suresh K., Christ University, Computer Science Department, Bangalore, India; Cynthia T., Christ University, Computer Science Department, Bangalore, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 979-833155691-4;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/IC3ECSBHI67834.2026.11469137

https://www.scopus.com/pages/publications/105038085126?origin=resultslist