D-Wave Quantum Inc. underperforms peers on return and volatility metrics and remains more unpredictable than other pure-play quantum companies, but investor pessimism is exaggerated. Recent revenue ...

Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the ...

With the rapid development of electronic networks, consumer online purchasing behavior data presents massive growth and diverse characteristics. How to accurately predict purchasing behavior based on ...

A professional TF-IDF + Logistic Regression style-risk classifier for educational fake-news detection, with a Streamlit dashboard, honest evaluation, uncertainty handling, and leakage analysis. An end ...

Have you ever imagined predicting your company’s revenue for the coming months based on past data? This is the power of time series forecasting, which analyzes data organized chronologically, such as ...

In this study, we investigate the feasibility of using deep learning for stock market prediction and technical analysis. We explore the dynamics of the stock market and prominent classical methods and ...

1 Information System Department, Faculty of Commerce and Business Administration Helwan University, Cairo, Egypt. 2 Computer Science Department, Faculty of Computer and Artificial Intelligence, Helwan ...

In this guide, we’ll explore the step-by-step process of using Python, LSTM, and technical indicators to predict ETF prices, covering everything from data preparation to model evaluation. Introduction ...

The research focuses on improving predictive accuracy in the financial sector through the exploration of machine learning algorithms for stock price prediction. The research follows an organized ...

The aims of this study are to predict the stock price trend in the stock market in an emerging economy. Using the Long Short Term Memory (LSTM) algorithm, and the corresponding technical analysis ...