A review on recent advancements in forex currency prediction
In recent years, the foreign exchange (FOREX) market has attracted quite a lot of scrutiny
from researchers all over the world. Due to its vulnerable characteristics, different types of …
from researchers all over the world. Due to its vulnerable characteristics, different types of …
[HTML][HTML] Foreign exchange currency rate prediction using a GRU-LSTM hybrid network
The foreign exchange (FOREX) market is one of the biggest financial markets in the world.
More than 5.1 trillion dollars are traded each day in the FOREX market by banks, retail …
More than 5.1 trillion dollars are traded each day in the FOREX market by banks, retail …
Forecasting returns with machine learning and optimizing global portfolios: evidence from the Korean and US stock markets
D Chun, J Kang, J Kim - Financial Innovation, 2024 - Springer
This study employs a variety of machine learning models and a wide range of economic and
financial variables to enhance the forecasting accuracy of the Korean won–US dollar …
financial variables to enhance the forecasting accuracy of the Korean won–US dollar …
Should deep learning models be in high demand, or should they simply be a very hot topic? A comprehensive study for exchange rate forecasting
Exchange rate movements can significantly impact not only foreign trade, capital flows, and
asset portfolio management, but also real economic activity. Therefore, the forecast of …
asset portfolio management, but also real economic activity. Therefore, the forecast of …
Refinement of ensemble strategy for acute lymphoblastic leukemia microscopic images using hybrid CNN-GRU-BiLSTM and MSVM classifier
Acute lymphocytic leukemia (ALL) is a common serious cancer in white blood cells (WBC)
that advances quickly and produces abnormal cells in the bone marrow. Cancerous cells …
that advances quickly and produces abnormal cells in the bone marrow. Cancerous cells …
Forex market forecasting with two-layer stacked Long Short-Term Memory neural network (LSTM) and correlation analysis
M Ayitey Junior, P Appiahene, O Appiah - Journal of Electrical Systems …, 2022 - Springer
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 …
Foreign exchange prediction using CEEMDAN and improved FA-LSTM
In Foreign Exchange (Forex) Prediction with high accuracy it becomes a challenge because
time series data has chaotic characteristics, uncertainty, and complexity. To improve the …
time series data has chaotic characteristics, uncertainty, and complexity. To improve the …
Comparative Analysis of Software Reliability Prediction Using Machine Learning and Deep Learning
A Jindal, A Gupta - … on Artificial Intelligence and Smart Energy …, 2022 - ieeexplore.ieee.org
Software Reliability is an integral part to determine Software Quality. Software is considered
to be of high quality if its reliability is high. There exist many statistical models that can help …
to be of high quality if its reliability is high. There exist many statistical models that can help …
Exchange rates forecasting and trend analysis after the COVID-19 outbreak: new evidence from interpretable machine learning
Z Su, X Cai, Y Wu - Applied Economics Letters, 2023 - Taylor & Francis
We investigate the predictability of 12 exchange rates with machine learning, Deep Learning
and interpretable machine learning (IML) models, based on a daily dataset from December …
and interpretable machine learning (IML) models, based on a daily dataset from December …
[PDF][PDF] An application of deep learning for exchange rate forecasting
This paper examines the performance of several state-of-the-art deep learning techniques
for exchange rate forecasting (deep feedforward network, convolutional network and a long …
for exchange rate forecasting (deep feedforward network, convolutional network and a long …