Effect of public sentiment on stock market movement prediction during the COVID-19 outbreak
Forecasting the stock market is one of the most difficult undertakings in the financial industry
due to its complex, volatile, noisy, and nonparametric character. However, as computer …
due to its complex, volatile, noisy, and nonparametric character. However, as computer …
A novel deep learning carbon price short-term prediction model with dual-stage attention mechanism
Carbon price prediction can help participants keep abreast of carbon market dynamics and
develop trading strategies. It is challenging for statistical models to accurately capture the …
develop trading strategies. It is challenging for statistical models to accurately capture the …
A hybrid convolutional recurrent (CNN-GRU) model for stock price prediction
Stock price forecasting systems are on-demand that used for prediction in the financial
world. The deep learning models are used for handling large data and making predictions …
world. The deep learning models are used for handling large data and making predictions …
Exploring the effectiveness of word embedding based deep learning model for improving email classification
Purpose Classifying emails as ham or spam based on their content is essential. Determining
the semantic and syntactic meaning of words and putting them in a high-dimensional feature …
the semantic and syntactic meaning of words and putting them in a high-dimensional feature …
Prediction of Course Grades in Computer Science Higher Education Program Via a Combination of Loss Functions in LSTM Model
In the realm of education, the timely identification of potential challenges, such as learning
difficulties leading to dropout risks, and the facilitation of personalized learning, emphasizes …
difficulties leading to dropout risks, and the facilitation of personalized learning, emphasizes …
[PDF][PDF] Time Series Forecasting Model for the Stock Market using LSTM and SVR.
Time series data prediction is an essential area of research in finance, and economics,
among others. It involves analyzing and modeling data collected over time to make future …
among others. It involves analyzing and modeling data collected over time to make future …
Analysing the Impact of News Polarity on Stock Market Price Forecasting
A Heidarian, NHAH Malin - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Stock market price prediction has always been a point of interests for researchers. Although
some financial indicators, can help to get a vague idea about stock price fluctuations, it still …
some financial indicators, can help to get a vague idea about stock price fluctuations, it still …
Applying Deep Learning for Stock Chart-Based Stock Market Trend Forecasting
E Chatziloizos, D Gunopulos - Intelligent Systems Conference, 2024 - Springer
This research explores an innovative three-step approach to stock market forecasting
through deep learning, using Convolutional Neural Networks (CNNs) and Long Short-Term …
through deep learning, using Convolutional Neural Networks (CNNs) and Long Short-Term …