A systematic review of fundamental and technical analysis of stock market predictions
The stock market is a key pivot in every growing and thriving economy, and every investment
in the market is aimed at maximising profit and minimising associated risk. As a result …
in the market is aimed at maximising profit and minimising associated risk. As a result …
Computational intelligence and financial markets: A survey and future directions
RC Cavalcante, RC Brasileiro, VLF Souza… - Expert Systems with …, 2016 - Elsevier
Financial markets play an important role on the economical and social organization of
modern society. In these kinds of markets, information is an invaluable asset. However, with …
modern society. In these kinds of markets, information is an invaluable asset. However, with …
Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach
Financial technology (Fintech) makes a significant contribution to the financial system by
reducing costs, providing higher quality services and increasing customer satisfaction …
reducing costs, providing higher quality services and increasing customer satisfaction …
Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach
OB Sezer, AM Ozbayoglu - Applied Soft Computing, 2018 - Elsevier
Computational intelligence techniques for financial trading systems have always been quite
popular. In the last decade, deep learning models start getting more attention, especially …
popular. In the last decade, deep learning models start getting more attention, especially …
A comprehensive evaluation of ensemble learning for stock-market prediction
Stock-market prediction using machine-learning technique aims at developing effective and
efficient models that can provide a better and higher rate of prediction accuracy. Numerous …
efficient models that can provide a better and higher rate of prediction accuracy. Numerous …
A survey on evolutionary machine learning
Artificial intelligence (AI) emphasises the creation of intelligent machines/systems that
function like humans. AI has been applied to many real-world applications. Machine …
function like humans. AI has been applied to many real-world applications. Machine …
A new hybrid ensemble deep reinforcement learning model for wind speed short term forecasting
Wind speed forecasting is a promising solution to improve the efficiency of energy utilization.
In this study, a novel hybrid wind speed forecasting model is proposed. The whole modeling …
In this study, a novel hybrid wind speed forecasting model is proposed. The whole modeling …
Stock market forecasting using computational intelligence: A survey
Stock market plays a key role in economical and social organization of a country. Stock
market forecasting is highly demanding and most challenging task for investors, professional …
market forecasting is highly demanding and most challenging task for investors, professional …
Predicting the direction of stock markets using optimized neural networks with Google Trends
H Hu, L Tang, S Zhang, H Wang - Neurocomputing, 2018 - Elsevier
The stock market is affected by many factors, such as political events, general economic
conditions, and traders' expectations. Predicting the direction of stock markets movement …
conditions, and traders' expectations. Predicting the direction of stock markets movement …
[HTML][HTML] DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring
Credit scoring (CS) is an effective and crucial approach used for risk management in banks
and other financial institutions. It provides appropriate guidance on granting loans and …
and other financial institutions. It provides appropriate guidance on granting loans and …