… techniques for enhancing financial forecasting capabilities. … financial forecasting, exploring
the role of soft computing techniques in harnessing the power of AI for data-driven financial …

… data, and focused on financial applications. Numerous studies applying GARCH and its
expansion methods to various contexts aside from financial data have been conducted. Several …

… covering financial time series forecasting and trading systems using traditional soft computing
… , focusing on DL implementations of financial time series forecasting. Our motivation is two-…

… use of intelligent techniques to financial time series prediction … also known as soft computing
techniques exclusively to the … of various Soft Computing hybrid forecasting models for …

… of soft computing techniques (especially fuzzy sets, artificial neural network, and evolutionary
computing) in time series forecasting. … problems of time series forecasting in depth, starting …

… health barriers and financial issues in different parts of the world. The forecast on COVID-19 …
Artificial Neural Networks (ANN) have generally been used for classification and forecasting …

… Most of the intelligent soft computing techniques are developed … The main intention of
forecasting is to reduce the risk in … The problem of trade industry and financial forecasting have …

… forecasting regional financial performance has spurred the emergence of various applications
of soft computing … of hybrid models that employ diverse soft computing techniques. In this …

… on financial time series volatility forecasting models involving RF, QRRF, and QRNN. We
also presented the application of these volatility forecasting models on eight financial time …

… The aim of this study, therefore, is to show whether GBLM would be valid for forecasting
financial indicators. First, the hidden pattern behind the change in each financial indicator was …