Ai in finance: challenges, techniques, and opportunities
L Cao - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
AI in finance refers to the applications of AI techniques in financial businesses. This area has
attracted attention for decades, with both classic and modern AI techniques applied to …
attracted attention for decades, with both classic and modern AI techniques applied to …
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 …
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 …
Stock market prediction using machine learning techniques: a decade survey on methodologies, recent developments, and future directions
With the advent of technological marvels like global digitization, the prediction of the stock
market has entered a technologically advanced era, revamping the old model of trading …
market has entered a technologically advanced era, revamping the old model of trading …
A novel graph convolutional feature based convolutional neural network for stock trend prediction
W Chen, M Jiang, WG Zhang, Z Chen - Information Sciences, 2021 - Elsevier
Stock trend prediction is one of the most widely investigated and challenging problems for
investors and researchers. Since the convolutional neural network (CNN) was introduced to …
investors and researchers. Since the convolutional neural network (CNN) was introduced to …
Learning-based stock trending prediction by incorporating technical indicators and social media sentiment
Stock trending prediction is a challenging task due to its dynamic and nonlinear
characteristics. With the development of social platform and artificial intelligence (AI) …
characteristics. With the development of social platform and artificial intelligence (AI) …
Causality-guided multi-memory interaction network for multivariate stock price movement prediction
Over the past few years, we've witnessed an enormous interest in stock price movement
prediction using AI techniques. In recent literature, auxiliary data has been used to improve …
prediction using AI techniques. In recent literature, auxiliary data has been used to improve …
[PDF][PDF] A study on classification and detection of small moths using CNN model.
SH Lee - Computers, Materials & Continua, 2022 - cdn.techscience.cn
Currently, there are many limitations to classify images of small objects. In addition, there are
limitations such as error detection due to external factors, and there is also a disadvantage …
limitations such as error detection due to external factors, and there is also a disadvantage …
YOLO object recognition algorithm and “buy-sell decision” model over 2D candlestick charts
Earning via real-time predictions with the experience in the visible trend directions of an
investment instrument in the past requires a different perspective on charts. Indicators and …
investment instrument in the past requires a different perspective on charts. Indicators and …