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 …
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, revam** the old model of trading …
market has entered a technologically advanced era, revam** the old model of trading …
Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong
Stock prediction via market data analysis is an attractive research topic. Both stock prices
and news articles have been employed in the prediction processes. However, how to …
and news articles have been employed in the prediction processes. However, how to …
A systematic review of stock market prediction using machine learning and statistical techniques
The stock market prediction patterns are seen as an important activity and it is more
effective. Hence, stock prices will lead to lucrative profits from sound taking decisions …
effective. Hence, stock prices will lead to lucrative profits from sound taking decisions …
Water quality prediction for smart aquaculture using hybrid deep learning models
Water quality prediction (WQP) plays an essential role in water quality management for
aquaculture to make aquaculture production profitable and sustainable. In this work, we …
aquaculture to make aquaculture production profitable and sustainable. In this work, we …
Machine learning approaches in stock market prediction: A systematic literature review
LN Mintarya, JNM Halim, C Angie, S Achmad… - Procedia Computer …, 2023 - Elsevier
Predicting the stock market has been done for a long time using traditional methods by
analyzing fundamental and technical aspects. With machine learning, stock market …
analyzing fundamental and technical aspects. With machine learning, stock market …
Deep attentive learning for stock movement prediction from social media text and company correlations
In the financial domain, risk modeling and profit generation heavily rely on the sophisticated
and intricate stock movement prediction task. Stock forecasting is complex, given the …
and intricate stock movement prediction task. Stock forecasting is complex, given the …
Machine learning stock market prediction studies: review and research directions
TJ Strader, JJ Rozycki, TH Root… - Journal of …, 2020 - scholarworks.lib.csusb.edu
Stock market investment strategies are complex and rely on an evaluation of vast amounts of
data. In recent years, machine learning techniques have increasingly been examined to …
data. In recent years, machine learning techniques have increasingly been examined to …
Scientometric review and analysis of recent approaches to stock market forecasting: Two decades survey
Abstract Stock Market Forecasting (SMF) has become a spotlighted area and is receiving
increasing attention due to the potential that investment returns can generate profound …
increasing attention due to the potential that investment returns can generate profound …
Benchmark dataset for mid‐price forecasting of limit order book data with machine learning methods
Managing the prediction of metrics in high‐frequency financial markets is a challenging task.
An efficient way is by monitoring the dynamics of a limit order book to identify the information …
An efficient way is by monitoring the dynamics of a limit order book to identify the information …