A survey of forex and stock price prediction using deep learning
Predictions of stock and foreign exchange (Forex) have always been a hot and profitable
area of study. Deep learning applications have been proven to yield better accuracy and …
area of study. Deep learning applications have been proven to yield better accuracy and …
[HTML][HTML] Data-driven stock forecasting models based on neural networks: A review
As a core branch of financial forecasting, stock forecasting plays a crucial role for financial
analysts, investors, and policymakers in managing risks and optimizing investment …
analysts, investors, and policymakers in managing risks and optimizing investment …
Forex market forecasting using machine learning: Systematic Literature Review and meta-analysis
Background When you make a forex transaction, you sell one currency and buy another. If
the currency you buy increases against the currency you sell, you profit, and you do this …
the currency you buy increases against the currency you sell, you profit, and you do this …
Phage_UniR_LGBM: phage virion proteins classification with UniRep features and LightGBM model
W Bao, Q Cui, B Chen, B Yang - … and mathematical methods in …, 2022 - Wiley Online Library
Phage, the most prevalent creature on the planet, serves a variety of critical roles. Phage's
primary role is to facilitate gene‐to‐gene communication. The phage proteins can be …
primary role is to facilitate gene‐to‐gene communication. The phage proteins can be …
Text mining of stocktwits data for predicting stock prices
M Jaggi, P Mandal, S Narang, U Naseem… - Applied System …, 2021 - mdpi.com
Stock price prediction can be made more efficient by considering the price fluctuations and
understanding people's sentiments. A limited number of models understand financial jargon …
understanding people's sentiments. A limited number of models understand financial jargon …
Stock price prediction based on LSTM and LightGBM hybrid model
L Tian, L Feng, L Yang, Y Guo - The Journal of Supercomputing, 2022 - Springer
Finding an accurate, stable and effective model to predict the rise and fall of stocks has
become a task increasingly favored by scholars. This paper proposes a long short-term …
become a task increasingly favored by scholars. This paper proposes a long short-term …
Feature learning for stock price prediction shows a significant role of analyst rating
J Singh, M Khushi - Applied system innovation, 2021 - mdpi.com
Efficient Market Hypothesis states that stock prices are a reflection of all the information
present in the world and generating excess returns is not possible by merely analysing trade …
present in the world and generating excess returns is not possible by merely analysing trade …
Event-driven LSTM for forex price prediction
The majority of studies in the field of AI guided financial trading focus on applying machine
learning algorithms to continuous historical price and technical analysis data. However, due …
learning algorithms to continuous historical price and technical analysis data. However, due …
An enhanced wasserstein generative adversarial network with gramian angular fields for efficient stock market prediction during market crash periods
At the beginning of 2020, the COVID-19 pandemic caused a sharp decline in equity market
indices, which remained stagnant for a considerable period. This resulted in significant …
indices, which remained stagnant for a considerable period. This resulted in significant …
Forex market forecasting with two-layer stacked Long Short-Term Memory neural network (LSTM) and correlation analysis
Since it is one of the world's most significant financial markets, the foreign exchange (Forex)
market has attracted a large number of investors. Accurately anticipating the forex trend has …
market has attracted a large number of investors. Accurately anticipating the forex trend has …