Financial time series forecasting with deep learning: A systematic literature review: 2005–2019
Financial time series forecasting is undoubtedly the top choice of computational intelligence
for finance researchers in both academia and the finance industry due to its broad …
for finance researchers in both academia and the finance industry due to its broad …
A survey of forex and stock price prediction using deep learning
Predictions of stock and foreign exchange (Forex) have always been a hot and profitable
area of study. Deep learning applications have been proven to yield better accuracy and …
area of study. Deep learning applications have been proven to yield better accuracy and …
Applications of deep learning in stock market prediction: recent progress
W Jiang - Expert Systems with Applications, 2021 - Elsevier
Stock market prediction has been a classical yet challenging problem, with the attention from
both economists and computer scientists. With the purpose of building an effective prediction …
both economists and computer scientists. With the purpose of building an effective prediction …
Deep learning for financial applications: A survey
Computational intelligence in finance has been a very popular topic for both academia and
financial industry in the last few decades. Numerous studies have been published resulting …
financial industry in the last few decades. Numerous studies have been published resulting …
News-based intelligent prediction of financial markets using text mining and machine learning: A systematic literature review
MN Ashtiani, B Raahemi - Expert Systems with Applications, 2023 - Elsevier
Researchers and practitioners have attempted to predict the financial market by analyzing
textual (eg, news articles and social media) and numeric data (eg, hourly stock prices, and …
textual (eg, news articles and social media) and numeric data (eg, hourly stock prices, and …
Multivariate time series forecasting via attention-based encoder–decoder framework
Time series forecasting is an important technique to study the behavior of temporal data and
forecast future values, which is widely applied in many fields, eg air quality forecasting …
forecast future values, which is widely applied in many fields, eg air quality forecasting …
A graph-based CNN-LSTM stock price prediction algorithm with leading indicators
In today's society, investment wealth management has become a mainstream of the
contemporary era. Investment wealth management refers to the use of funds by investors to …
contemporary era. Investment wealth management refers to the use of funds by investors to …
A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions
A Thakkar, K Chaudhari - Expert Systems with Applications, 2021 - Elsevier
The stock market has been an attractive field for a large number of organizers and investors
to derive useful predictions. Fundamental knowledge of stock market can be utilised with …
to derive useful predictions. Fundamental knowledge of stock market can be utilised with …
A deep reinforcement learning based method for real-time path planning and dynamic obstacle avoidance
P Chen, J Pei, W Lu, M Li - Neurocomputing, 2022 - Elsevier
In a dynamic environment, the moving obstacle makes the path planning of the manipulator
very difficult. Therefore, this paper proposes a path planning with dynamic obstacle …
very difficult. Therefore, this paper proposes a path planning with dynamic obstacle …
Stock market analysis: A review and taxonomy of prediction techniques
D Shah, H Isah, F Zulkernine - International Journal of Financial Studies, 2019 - mdpi.com
Stock market prediction has always caught the attention of many analysts and researchers.
Popular theories suggest that stock markets are essentially a random walk and it is a fool's …
Popular theories suggest that stock markets are essentially a random walk and it is a fool's …