[HTML][HTML] Forecasting stock market prices using machine learning and deep learning models: A systematic review, performance analysis and discussion of implications

G Sonkavde, DS Dharrao, AM Bongale… - International Journal of …, 2023 - mdpi.com
The financial sector has greatly impacted the monetary well-being of consumers, traders,
and financial institutions. In the current era, artificial intelligence is redefining the limits of the …

Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022

C Zhang, NNA Sjarif, R Ibrahim - … Reviews: Data Mining and …, 2024 - Wiley Online Library
Accurately predicting the prices of financial time series is essential and challenging for the
financial sector. Owing to recent advancements in deep learning techniques, deep learning …

[HTML][HTML] Predicting stock market index using LSTM

HN Bhandari, B Rimal, NR Pokhrel, R Rimal… - Machine Learning with …, 2022 - Elsevier
The rapid advancement in artificial intelligence and machine learning techniques,
availability of large-scale data, and increased computational capabilities of the machine …

[HTML][HTML] The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction

P Chhajer, M Shah, A Kshirsagar - Decision Analytics Journal, 2022 - Elsevier
The future is unknown and uncertain, but there are ways to predict future events and reap
the rewards safely. One such opportunity is the application of machine learning and artificial …

Wavelet-Seq2Seq-LSTM with attention for time series forecasting of level of dams in hydroelectric power plants

SF Stefenon, LO Seman, LS Aquino… - Energy, 2023 - Elsevier
Reservoir level control in hydroelectric power plants has importance for the stability of the
electric power supply over time and can be used for flood control. In this sense, this paper …

COVID-19 prediction and detection using deep learning

M Alazab, A Awajan, A Mesleh… - International Journal of …, 2020 - cspub-ijcisim.org
Currently, the detection of coronavirus disease 2019 (COVID-19) is one of the main
challenges in the world, given the rapid spread of the disease. Recent statistics indicate that …

Stock market forecasting using a multi-task approach integrating long short-term memory and the random forest framework

HJ Park, Y Kim, HY Kim - Applied Soft Computing, 2022 - Elsevier
Numerous studies have adopted deep learning (DL) in financial market forecasting models
owing to its superior performance. The DL models require as many relevant input variables …

[HTML][HTML] Predicting financial performance for listed companies in Thailand during the transition period: A class-based approach using logistic regression and random …

P Supsermpol, S Thajchayapong… - Journal of open …, 2023 - Elsevier
This study presents a class-based approach developed to evaluate the financial
performance of companies that have undergone public listing on the stock market. By …

Predicting stock market using machine learning: best and accurate way to know future stock prices

D Sheth, M Shah - International Journal of System Assurance Engineering …, 2023 - Springer
Dissatisfaction is the first step of progress, this statement serves to be the base of using
Artifcial Intelligence in predicting stock prices. A great deal of people dreamed of predicting …

A hybrid approach of adaptive wavelet transform, long short-term memory and ARIMA-GARCH family models for the stock index prediction

M Zolfaghari, S Gholami - Expert Systems with Applications, 2021 - Elsevier
Modelling and forecasting the stock price constitute an important area of financial research
for both academics and practitioners. This study seeks to determine whether improvements …