Add to ORKGThe aim of the paper was to outline a trend prediction model for the BELEX15 stock market index of the Belgrade stock exchange based on Support Vector Machines (SVMs). The feature selection was carried out through the analysis of technical and macroeconomics indicators. In addition, the SVM method was compared with a "similar" one, the least squares support vector machines - LS-SVMs to analyze their classification precisions and complexity. The test results indicate that the SVMs outperform benchmarking models and are suitable for short-term stock market trend predictions
Due to non-linearity and non-stationary characteristics of stock market time series data, prior appr...
Abstract—Obtaining accurate prediction of stock index sig-nificantly helps decision maker to take co...
In recent years with the advent of computational power, Machine Learning has become a popular approa...
Financial markets facilitate international trade, are indicative of the future prospects of organiza...
In this study, a prediction model based on support vector machines (SVM) improved by introducing a v...
Previous research shows strong evidence that traditional regression based predictive models face sig...
This report depicts the work done by me, Abburu Manasa, as a contribution towards my Final Year Proj...
Stock market is a highly complex and non-linear dynamic system. Successful predictions in the stock ...
Prediction of stock trends is the most significant and challenging task for the enterprise as well a...
Today, time series data are predicted using various methods. The main technique currently used to id...
Prediction of the trend of the stock market is very crucial. If someone has robust forecasting tools...
A popular Machine Learning Technique called the Support Vector Machine (SVM) is adopted on the Stock...
Stock exchange trading has been utilized to gain profit by constantly buying and selling best-perfor...
Abstract: Time series forecasting is receiving remarkable attention from the research community in u...
Many machine learning approaches have been usedfor financial forecasting to estimate stock trends in...
Due to non-linearity and non-stationary characteristics of stock market time series data, prior appr...
Abstract—Obtaining accurate prediction of stock index sig-nificantly helps decision maker to take co...
In recent years with the advent of computational power, Machine Learning has become a popular approa...
Financial markets facilitate international trade, are indicative of the future prospects of organiza...
In this study, a prediction model based on support vector machines (SVM) improved by introducing a v...
Previous research shows strong evidence that traditional regression based predictive models face sig...
This report depicts the work done by me, Abburu Manasa, as a contribution towards my Final Year Proj...
Stock market is a highly complex and non-linear dynamic system. Successful predictions in the stock ...
Prediction of stock trends is the most significant and challenging task for the enterprise as well a...
Today, time series data are predicted using various methods. The main technique currently used to id...
Prediction of the trend of the stock market is very crucial. If someone has robust forecasting tools...
A popular Machine Learning Technique called the Support Vector Machine (SVM) is adopted on the Stock...
Stock exchange trading has been utilized to gain profit by constantly buying and selling best-perfor...
Abstract: Time series forecasting is receiving remarkable attention from the research community in u...
Many machine learning approaches have been usedfor financial forecasting to estimate stock trends in...
Due to non-linearity and non-stationary characteristics of stock market time series data, prior appr...
Abstract—Obtaining accurate prediction of stock index sig-nificantly helps decision maker to take co...
In recent years with the advent of computational power, Machine Learning has become a popular approa...