Forecasting the stock market with deep neural networks is a trend nowadays. However, the results are very different between different models as well as within the same model with different architecture. Therefore, a careful research should be done on choosing type of model and selecting the architecture of the model. Also, hyper-parameters should be properly selected based on type of data and a nature of the problem. A lot of researches have been done on Bursa Malaysia stock market and different algorithms have been tests in the past. Therefore, this paper objective is to use the latest deep learning time series model known as long-short term memory to forecast the stock prices of the Malaysian largest stock market
Price prediction has become a major task due to the explosive increase in the number of investors. T...
Stock market is an important element in business as it may contribute to profit or loss in a company...
A stock trend prediction has been in the spotlight from the past to the present. Fortunately, there ...
The challenging task of predicting stock value need a solid algorithmic framework to determine longe...
Accurate prediction of stock prices plays an increasingly prominent role in the stock market where r...
Forecasting stock price is a challenging topic for the researchers by the way of statistics or in ne...
Forecasting stock price is a challenging topic for the researchers by the way of statistics or in ne...
The study proposes the use of a stacked Long-Short-Term Memory (LSTM) model to predict the KSE-100 s...
As part of a financial institution, the stock market has been an essential factor in the growth and ...
This study attempts to predict stock index prices using multivariate time series analysis. The study...
In the financial world, the forecasting of stock price gains significant attraction. For the growth ...
As one of the most popular financial market instruments, the stock has formed one of the most massiv...
The stock market is known for its extreme complexity and volatility, and people are always looking f...
The Indonesian Stock Exchange (IDX) stock market index is one of the main indicators commonly used a...
This research explores the application of four deep learning architectures—Multilayer Perceptron (ML...
Price prediction has become a major task due to the explosive increase in the number of investors. T...
Stock market is an important element in business as it may contribute to profit or loss in a company...
A stock trend prediction has been in the spotlight from the past to the present. Fortunately, there ...
The challenging task of predicting stock value need a solid algorithmic framework to determine longe...
Accurate prediction of stock prices plays an increasingly prominent role in the stock market where r...
Forecasting stock price is a challenging topic for the researchers by the way of statistics or in ne...
Forecasting stock price is a challenging topic for the researchers by the way of statistics or in ne...
The study proposes the use of a stacked Long-Short-Term Memory (LSTM) model to predict the KSE-100 s...
As part of a financial institution, the stock market has been an essential factor in the growth and ...
This study attempts to predict stock index prices using multivariate time series analysis. The study...
In the financial world, the forecasting of stock price gains significant attraction. For the growth ...
As one of the most popular financial market instruments, the stock has formed one of the most massiv...
The stock market is known for its extreme complexity and volatility, and people are always looking f...
The Indonesian Stock Exchange (IDX) stock market index is one of the main indicators commonly used a...
This research explores the application of four deep learning architectures—Multilayer Perceptron (ML...
Price prediction has become a major task due to the explosive increase in the number of investors. T...
Stock market is an important element in business as it may contribute to profit or loss in a company...
A stock trend prediction has been in the spotlight from the past to the present. Fortunately, there ...