As financial markets become increasingly complex and dynamic, the application of machine
learning (ML) techniques for stock market forecasting has garnered significant attention. This …

Since market uncertainty, or volatility, serves as a crucial gauge for assessing the traits of
market fluctuations, the link between stock market volume and price continues to be a focal …

Purpose This study aims to provide the best estimate of a stock's next day's closing price for
a given day with the help of the hidden Markov model–Gaussian mixture model (HMM …

In recent years, machine learning (ML) has brought effective approaches and novel
techniques to economic decision, investment forecasting, and risk management, etc., coping …

Many forecasting techniques have been put forth and used in recent years to predict stock
market trends. Recently, many researchers developed models based on Artificial Neural …

The stock market is financial market where stocks of openly listed corporations are bought
and sold. It is needle of economic health of country, reflects the company performance and …

In the ever-evolving landscape of financial markets, the pursuit of accurate stock price
predictions remains a formidable challenge. This study addresses the challenge of profitable …

Nowadays, many advanced models have been used for time series forecasting, two of the
typical models are Informer and Long Short-Term Memory (LSTM). Stock price forecasting is …

Investing in the stock market has never been an easy task. This paper develops a stock
recommendation and trade assistance that uses the past performance of the stock to predict …

Predicting share prices is crucial in financial markets for traders and portfolio managers. This
study employs hidden Markov modeling, focusing on three key parameters: initial probability …