Trend Prediction of DJIA index based on News Extraction from Yahoo Finance

Decision making in a financial world is a very challenging task for any investor as it can leads towards a very heavy loss as well as very higher returns.Therefore, proper understanding of market behavior is required.It is found in research that movement of prices in financial market is random in nature and depends on multiple factors.In this research sentiment-based prediction of DJIA (Dow Jones Industrial Average) index is performed to forecast the future direction of the indices.The objective behind this research is to analyze if the market is sensitive to news or not and if the web news data contributes in the movement of the market.Five different classification models of machine learning are used which include decision tree, random forest, support vector machine, K-Nearest Neighbor and logistic regression.It is observed that KNN is the best predictive model among all for our dataset with the accuracy of 70%.The results are validated on NASDAQ composite and proved that KNN outperforms other considered classifiers.

Authors

Institutions

Publication Details

Journal
International Journal of Computer Applications
Published
2025-02-03
DOI
https://doi.org/10.5120/ijca2025924379
Citations
3
Primary Topic
Diverse Approaches in Healthcare and Education Studies
Type
article
Field-Weighted Citation Impact
5.64
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trend Prediction of DJIA index based on News Extraction from Yahoo Finance

Ubaida Fatima, Komal Batool, Mirza Faizan Ahmed
3 citations
International Journal of Computer Applications
Diverse Approaches in Healthcare and Education Studies
5.64
article

Trend Prediction of DJIA index based on News Extraction from Yahoo Finance

Ubaida Fatima, Komal Batool, Mirza Faizan Ahmed
article en
3 citations

Abstract

Decision making in a financial world is a very challenging task for any investor as it can leads towards a very heavy loss as well as very higher returns.Therefore, proper understanding of market behavior is required.It is found in research that movement of prices in financial market is random in nature and depends on multiple factors.In this research sentiment-based prediction of DJIA (Dow Jones Industrial Average) index is performed to forecast the future direction of the indices.The objective behind this research is to analyze if the market is sensitive to news or not and if the web news data contributes in the movement of the market.Five different classification models of machine learning are used which include decision tree, random forest, support vector machine, K-Nearest Neighbor and logistic regression.It is observed that KNN is the best predictive model among all for our dataset with the accuracy of 70%.The results are validated on NASDAQ composite and proved that KNN outperforms other considered classifiers.

International Journal of Computer ApplicationsVol. 186(64)
NED University of Engineering and Technology (PK)
Decent work and economic growth
Openalex Percentile: Top 5%
Diverse Approaches in Healthcare and Education Studies
5.64
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Trend Prediction of DJIA index based on News Extraction from Yahoo Finance — Ubaida Fatima, Komal Batool, et al. · International Journal of Computer Applications (2025) | TGRS Research Map | TGRS