Articles via Databases
Articles via Journals
Online Catalog
E-books
Research & Information Literacy
Interlibrary loan
Theses & Dissertations
Collections
Policies
Services
About / Contact Us
Administration
Littman Architecture Library
This site will be removed in January 2019, please change your bookmarks.
This page will redirect to https://digitalcommons.njit.edu/theses/1841/ in 5 seconds

The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title: Stock market prediction using investor sentiment
Author: Shukla, Sarvesh
View Online: njit-etd2021-029
(x, 57 pages ~ 1.9 MB pdf)
Department: Department of Computer Science
Degree: Master of Science
Program: Computer Science
Document Type: Thesis
Advisory Committee: Wang, Guiling (Committee chair)
Koutis, Ioannis (Committee member)
Martin-Utrera, Alberto (Committee member)
Date: 2021-05
Keywords: Investor sentiment
LSTM
GRU
Deep learning
Availability: Unrestricted
Abstract:

Stock market prediction has attracted not only business but academia as well. It is a research topic, to which many computational methods have been proposed, but desirable and reliable performance is yet to be attained. This study proposes a new method for stock market prediction, which adopts the Gated Recurrent Unit a deep neural network and incorporates investor sentiment to improve its forecasting performance. By extracting investor sentiment from news headlines using VADER sentiment, this paper makes it possible to analyze the irrational component of stock price. Our empirical study on DJIA index proves that our prediction method provides 6% better prediction compared to baseline models. Furthermore, our empirical study helps to better understand investor sentiment and stock behaviors. Finally, this work shows the potential of deep learning in forecasting a financial time series in the presence of strong noises.


If you have any questions please contact the ETD Team, libetd@njit.edu.

 
ETD Information
Digital Commons @ NJIT
Theses and DIssertations
ETD Policies & Procedures
ETD FAQ's
ETD home

Request a Scan
NDLTD

NJIT's ETD project was given an ACRL/NJ Technology Innovation Honorable Mention Award in spring 2003