Abstract Stock Market Forecasting (SMF) has become a spotlighted area and is receiving
increasing attention due to the potential that investment returns can generate profound …

The literature on stock forecasting using the innovative technique of Artificial Intelligence (AI)
has become overwhelming, making it quite challenging for academics and relevant …

This study investigates stock market indices prediction that is an interesting and important
research in the areas of investment and applications, as it can get more profits and returns at …

Numerous studies have adopted deep learning (DL) in financial market forecasting models
owing to its superior performance. The DL models require as many relevant input variables …

Stock market prediction is regarded as a challenging task in financial time-series
forecasting. The central idea to successful stock market prediction is achieving best results …

This paper proposes a hybridized framework of Support Vector Machine (SVM) with K-
Nearest Neighbor approach for Indian stock market indices prediction. The objective of this …

Managing the prediction of metrics in high‐frequency financial markets is a challenging task.
An efficient way is by monitoring the dynamics of a limit order book to identify the information …

Time series data are data which are taken in a particular time interval, and may vary
drastically during the period of observation and hence it becomes highly nonlinear. Stock …

Stock market prediction is of great interest to stock traders and investors due to high profit in
trading the stocks. A successful stock buying/selling generally occurs near price trend …

Financial markets are complex systems influenced by many interrelated economic, political
and psychological factors and characterised by inherent nonlinearities. Recently, there have …