A Machine Learning Approach for Revving Up Revenue of Indian Tech Companies

Title

A Machine Learning Approach for Revving Up Revenue of Indian Tech Companies

Creator

Tungar S.K.; Umme Salma M.

Description

This study addresses a critical gap in research by examining the effectiveness of various machine learning models in predicting revenue for Indian tech companies. The V.A.R, ARIMA, simple moving average, weighted moving average, and FB Prophet models were employed and their performances was compared. The findings demonstrate that FB Prophet consistently outperforms other models, exhibiting superior accuracy in revenue forecasting. This underscores FB Prophet's potential to offer precise revenue predictions, enabling companies to gain insights into their financial health, anticipate market trends, and optimize decision-making. Future research could further enhance accuracy by incorporating economic indicators, providing a more holistic view of revenue dynamics and empowering companies to make more informed strategic decisions. 2024 IEEE.

Source

2nd IEEE International Conference on Data Science and Information System, ICDSIS 2024

Date

2024-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

arima; fb prophet; indian tech companies; machine learning; revenue; v.a.r model

Coverage

Tungar S.K., Christ (Deemed To Be University), Department Of Statistics And Data Science, Karnataka, Bengaluru, India; Umme Salma M., Christ (Deemed To Be University), Department Of Statistics And Data Science, Karnataka, Bengaluru, India

Rights

Restricted Access

Relation

ISBN: 979-835038166-5

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICDSIS61070.2024.10594491

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200126947&doi=10.1109%2fICDSIS61070.2024.10594491&partnerID=40&md5=839ff3e2b69f9adccb24eb4e56707556