Framework for predicting and modeling stock market prices based on deep learning algorithms
The creation of trustworthy models of the equities market enables investors to make better-
informed choices. A trading model may lessen the risks that are connected with investing …
informed choices. A trading model may lessen the risks that are connected with investing …
[HTML][HTML] A novel deep learning technique for detecting emotional impact in online education
Emotional intelligence is the automatic detection of human emotions using various
intelligent methods. Several studies have been conducted on emotional intelligence, and …
intelligent methods. Several studies have been conducted on emotional intelligence, and …
[HTML][HTML] Forecasting stock prices of fintech companies of India using random forest with high-frequency data
The fintech segment is currently one of the most rapidly growing industries, attracting
numerous investors who anticipate substantial returns in the future. Notably, not only …
numerous investors who anticipate substantial returns in the future. Notably, not only …
Forecasting multistep daily stock prices for long-term investment decisions: A study of deep learning models on global indices
Deep machine learning algorithms play an important role in facilitating the development of
predictive models for the stock market. However, most studies focus on predicting next-day …
predictive models for the stock market. However, most studies focus on predicting next-day …
Predicting close price in emerging Saudi Stock Exchange: time series models
AH Al-Nefaie, THH Aldhyani - Electronics, 2022 - mdpi.com
The forecasting of stock prices is an important area of research because of the benefits it
provides for individuals, corporations, and governments. The purpose of this study is to …
provides for individuals, corporations, and governments. The purpose of this study is to …
[HTML][HTML] A new financial risk prediction model based on deep learning and quasi-oppositional coot algorithm
FM Alhomayani, KA Alruwaitee - Alexandria Engineering Journal, 2024 - Elsevier
Incorporating ground-breaking technologies such as deep learning (DL) has revolutionized
predictive modelling in the rapidly evolving landscape of the finance sector. DL approaches …
predictive modelling in the rapidly evolving landscape of the finance sector. DL approaches …
[HTML][HTML] An open innovative inventory management based demand forecasting approach for the steel industry
This research focuses on accurately forecasting steel wire mesh demand to ensure timely
order fulfillment. Various univariate time series forecasting methods were employed …
order fulfillment. Various univariate time series forecasting methods were employed …
Information environment quantifiers as investment analysis basis
DG Rodionov, PA Pashinina, EA Konnikov… - Economies, 2022 - mdpi.com
The combination of the processes of widespread digitalization and globalization of the world
economy has led to a significant expansion of the global information environment. The …
economy has led to a significant expansion of the global information environment. The …
Optimization of Traditional Stock Market Strategies Using the LSTM Hybrid Approach
Investment decision-makers increasingly rely on modern digital technologies to enhance
their strategies in today's rapidly changing and complex market environment. This paper …
their strategies in today's rapidly changing and complex market environment. This paper …
Predicting the Karachi Stock Price index with an Enhanced multi-layered Sequential Stacked Long-Short-Term Memory Model
The study proposes the use of a stacked Long-Short-Term Memory (LSTM) model to predict
the KSE-100 stock exchange trend and provides a comprehensive review of the literature on …
the KSE-100 stock exchange trend and provides a comprehensive review of the literature on …