ARTICLES

Filter  
Active filters 0
Remove
  

Refine your searches by:

Collections
Economy
Administration - Business
Education
Social Sciences
Agronomy and forestry
Technology
Research
Computing
Architecture and Urbanism
Pure sciences
all records (73)

Languages
English
Portuguese
Spanish
German
French

Countries
Indonesia
USA
Brazil
Ukraine
South Africa
Germany
Switzerland
Spain
Italy
Romania
all records (71)

Years
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
all records (24)

Filter  
 
31.538  Articles
1 of 3.155 pages  |  10  records  |  more records»
Bidirectional Long Short Term Memory (Bidirectional LSTM) is a machine learning technique with the ability to capture data context by traversing backward data to forward data and vice versa. However, the characteristics of stock data with large fluctuatio... see more

Stock price prediction is on the agenda of most researchers based on the uncertainty in its nature. In past two decades, the literature on the development of prediction models for stock prices has extended dramatically. These studies mostly focused on spe... see more

The stock market often attracts investors to invest, but it is not uncommon for investors to experience losses when buying and selling shares. This causes investors to hesitate to determine when to sell or buy shares in the stock market. The accurate stoc... see more

Stocks are one of the investment instruments that are currently in demand because they have a greater return value than saving in a bank. It's just that investing in stocks has the risk of decreasing the value of the stock price, which can make investors ... see more

In recent years, the application of deep learning-based financial modeling tools has grown in popularity. Research on stock forecasting is crucial to understanding how a nation's economy is doing. The study of intrinsic value and stock market forecasting ... see more

The financial industry has been becoming more and more dependent on advanced computing technologies in order to maintain competitiveness in a global economy. Hence, the stock price prediction problem using data mining techniques is one of the most importa... see more

Various bankruptcy prediction models have been used to measure the movement of stock prices, and thus the firms’ performance. This study is aimed at empirically exploring the usefulness of the Olhson, Almant Modification, Grover, Springate, and Zmijewski ... see more

Stock exchange trading has been utilized to gain profit by constantly buying and selling best-performing stocks in a short term. Deep knowledge, time dedication, and experience are essential for optimizing profit if stock price fluctuations are analyzed m... see more

Stock price prediction is a solution to reduce the risk of loss from investing in stocks go public. Although stock prices can be analyzed by stock experts, this analysis is analytical bias. Recurrent Neural Network (RNN) is a machine learning algorithm th... see more

1 of 3.155 pages  |  10  records  |  more records»