Short-term stock market price trend prediction using a comprehensive deep learning system
J Shen, MO Shafiq - Journal of big Data, 2020 - Springer
In the era of big data, deep learning for predicting stock market prices and trends has
become even more popular than before. We collected 2 years of data from Chinese stock …
become even more popular than before. We collected 2 years of data from Chinese stock …
Artificial intelligence in accounting and finance: Challenges and opportunities
Z Yi, X Cao, Z Chen, S Li - IEEE Access, 2023 - ieeexplore.ieee.org
The rapid expansion of artificial intelligence (AI) technologies presents novel technical
solutions to traditional accounting and finance problems. Despite this, scholars in …
solutions to traditional accounting and finance problems. Despite this, scholars in …
A survey on machine learning models for financial time series forecasting
Financial time series (FTS) are nonlinear, dynamic and chaotic. The search for models to
facilitate FTS forecasting has been highly pursued for decades. Despite major related …
facilitate FTS forecasting has been highly pursued for decades. Despite major related …
Prediction of cryptocurrency returns using machine learning
In this study, the predictability of the most liquid twelve cryptocurrencies are analyzed at the
daily and minute level frequencies using the machine learning classification algorithms …
daily and minute level frequencies using the machine learning classification algorithms …
Machine learning in finance: A topic modeling approach
We identify the core topics of research applying machine learning to finance. We use a
probabilistic topic modeling approach to make sense of this diverse body of research …
probabilistic topic modeling approach to make sense of this diverse body of research …
A stock series prediction model based on variational mode decomposition and dual-channel attention network
Due to the comprehensive impact of external factors (politics, economy, market, etc.) and
internal factors (organizational structure, management ability, innovation capability, etc.) …
internal factors (organizational structure, management ability, innovation capability, etc.) …
A novel hybrid model using teaching–learning-based optimization and a support vector machine for commodity futures index forecasting
SP Das, S Padhy - International Journal of Machine Learning and …, 2018 - Springer
The analysis and prediction of financial time-series data are difficult, and are the most
complicated tasks concerned with improving investment decisions. In this study, we …
complicated tasks concerned with improving investment decisions. In this study, we …
Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms—Support vector regression forecast combinations
The motivation of this paper is to introduce a hybrid Rolling Genetic Algorithm-Support
Vector Regression (RG-SVR) model for optimal parameter selection and feature subset …
Vector Regression (RG-SVR) model for optimal parameter selection and feature subset …
A hybrid model for exchange rate prediction
H Ince, TB Trafalis - Decision Support Systems, 2006 - Elsevier
Exchange rate forecasting is an important problem. Several forecasting techniques have
been proposed in order to gain some advantages. Most of them are either as good as …
been proposed in order to gain some advantages. Most of them are either as good as …
A novel hybrid model for stock price forecasting based on metaheuristics and support vector machine
This paper intends to present a new model for the accurate forecast of the stock's future
price. Stock price forecasting is one of the most complicated issues in view of the high …
price. Stock price forecasting is one of the most complicated issues in view of the high …