Optimizing Technical Analysis and Stock Price Analysis Using: BLRM-QNDNL-Reference-Cited by-同舟云学术

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Optimizing Technical Analysis and Stock Price Analysis Using: BLRM-QNDNL

Published:2023-12-13 Issue: Volume:4 Page:574-579
ISSN:
Container-title:2023 OITS International Conference on Information Technology (OCIT)
language:
Short-container-title:

Author:

Kalva Sudhakar¹,Naganjaneyulu Satuluri¹,K Sudhakar¹

Affiliation:

1. Jawaharlal Nehru Technological University, Kakinada, LakiReddy Bali Reddy College of Engineering (Autonomous) Mylavaram, G. Pulla Reddy Engineering College (Autonomous),Computer Science and Engineering,Department of Information Technology, Department of Computer Science and Engineering,Kurnool

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10430418/10430505/10430665.pdf?arnumber=10430665

Reference15 articles.

1. DeepClue: Visual Interpretation of Text-Based Deep Stock Prediction

2. Deep learning-based feature engineering for stock price movement prediction

3. Enhanced news sentiment analysis using deep learning methods

4. Stock market forecasting with financial micro-blog based on sentiment and time series analysis

5. A novel hybrid model based on Hodrick–Prescott filter and support vector regression algorithm for optimizing stock market price prediction

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