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 …
Stock Price prediction using LSTM and SVR
G Bathla - 2020 Sixth International Conference on Parallel …, 2020 - ieeexplore.ieee.org
Stock price movement is non-linear and complex. Several research works have been carried
out to predict stock prices. Traditional approaches such as Linear Regression and Support …
out to predict stock prices. Traditional approaches such as Linear Regression and Support …
A stock closing price prediction model based on CNN‐BiSLSTM
H Wang, J Wang, L Cao, Y Li, Q Sun, J Wang - Complexity, 2021 - Wiley Online Library
As the stock market is an important part of the national economy, more and more investors
have begun to pay attention to the methods to improve the return on investment and …
have begun to pay attention to the methods to improve the return on investment and …
Stocks of year 2020: prediction of high variations in stock prices using LSTM
Stock Market movement is highly volatile, complex, and non-linear. Several researchers
have proposed innovative approaches to predict stock price movement using traditional data …
have proposed innovative approaches to predict stock price movement using traditional data …
A Systematic Review on Graph Neural Network-based Methods for Stock Market Forecasting
Financial technology (FinTech) is a field that uses artificial intelligence to automate financial
services. One area of FinTech is stock analysis, which aims to predict future stock prices to …
services. One area of FinTech is stock analysis, which aims to predict future stock prices to …
Stock price movement prediction using sentiment analysis and CandleStick chart representation
TT Ho, Y Huang - Sensors, 2021 - mdpi.com
Determining the price movement of stocks is a challenging problem to solve because of
factors such as industry performance, economic variables, investor sentiment, company …
factors such as industry performance, economic variables, investor sentiment, company …
Stock market behaviour prediction using stacked LSTM networks
SO Ojo, PA Owolawi, M Mphahlele… - 2019 International …, 2019 - ieeexplore.ieee.org
Predicting the behavior of the stock market has been an area that has attracted the interest
of many researchers particularly in the field of Machine Learning and time series analysis …
of many researchers particularly in the field of Machine Learning and time series analysis …
A graph neural network-based stock forecasting method utilizing multi-source heterogeneous data fusion
X Li, J Wang, J Tan, S Ji, H Jia - Multimedia tools and applications, 2022 - Springer
The study of the prediction of stock market volatility is of great significance to rationally
control financial market risks and increase excessive investment returns and has received …
control financial market risks and increase excessive investment returns and has received …
Cost optimization for big data workloads based on dynamic scheduling and cluster-size tuning
Analytical data processing has become the cornerstone of today's businesses success, and
it is facilitated by Big Data platforms that offer virtually limitless scalability. However …
it is facilitated by Big Data platforms that offer virtually limitless scalability. However …
Integrating big data driven sentiments polarity and ABC-optimized LSTM for time series forecasting
Stock market is a dynamic and volatile market that is considered as time series data. The
growth of financial data exposed the computational efficiency of the conventional systems …
growth of financial data exposed the computational efficiency of the conventional systems …