TCLN: A Transformer-based Conv-LSTM network for multivariate time series forecasting
S Ma, T Zhang, YB Zhao, Y Kang, P Bai - Applied Intelligence, 2023 - Springer
The study of multivariate time series forecasting (MTSF) problems has high significance in
many areas, such as industrial forecasting and traffic flow forecasting. Traditional forecasting …
many areas, such as industrial forecasting and traffic flow forecasting. Traditional forecasting …
Cleaning Russian oil industry for energy resource exploration and industrial transformation towards zero carbon green recovery: Role of inclusive digital finance
Y Chen - Resources Policy, 2024 - Elsevier
This study is inspired by the pressing need to deal with environmental problems inherent to
Russia's oil sector and simultaneously encourage progress toward a zero-carbon green …
Russia's oil sector and simultaneously encourage progress toward a zero-carbon green …
Index tracking using shapley additive explanations and one-dimensional pointwise convolutional autoencoders
Y Zhang, J De Smedt - International Review of Financial Analysis, 2024 - Elsevier
The aim of index tracking is to mimic the performance of a benchmark index via minimizing
the tracking error between the returns of the market index and the tracking portfolio. Lately …
the tracking error between the returns of the market index and the tracking portfolio. Lately …
Hybridization of long short-term memory neural network in fractional time series modeling of inflation
Inflation is capable of significantly impacting monetary policy, thereby emphasizing the need
for accurate forecasts to guide decisions aimed at stabilizing inflation rates. Given the …
for accurate forecasts to guide decisions aimed at stabilizing inflation rates. Given the …
Neural networks and value at risk
Utilizing a generative regime switching framework, we perform Monte-Carlo simulations of
asset returns for Value at Risk threshold estimation. Using equity markets and long term …
asset returns for Value at Risk threshold estimation. Using equity markets and long term …
Dynamic spillover between crude oil, gold, and Chinese stock market sectors–analysis of spillovers during financial crisis data during the last two decades
YT Wu, C Mai - Heliyon, 2024 - cell.com
The present study investigates the presence of asymmetric return spillovers among crude oil
futures, gold futures, and ten Chinese stock sector markets. Time-varying asymmetric …
futures, gold futures, and ten Chinese stock sector markets. Time-varying asymmetric …
Comparative Risk Analysis and Price Prediction of Corporate Shares Using Deep Learning Models like LSTM and Machine Learning Models
M Mehdi, F Nasim, MQ Munir - Journal of Computing & Biomedical …, 2024 - jcbi.org
The prediction of share prices and risk analysis have always posed significant challenges
for investors due to the influence of various economic, financial, and political factors …
for investors due to the influence of various economic, financial, and political factors …
Tata Steel Stock Forecasting Using Deep Learning
Trend finding in Stock market is highly unpredictable due to the heavy buying and selling of
the stocks. Tata Steel holds the highest capital of the steel industry and it holds the heavy …
the stocks. Tata Steel holds the highest capital of the steel industry and it holds the heavy …
Application of LSTM, RNN, and Transformer in Stock Price Prediction of Information Technology Companies: A Comparative Analysis
PU Rukmana, H Fakhrurroja - 2024 International Conference …, 2024 - ieeexplore.ieee.org
This research presents a comparative analysis of the Long Short-Term Memory (LSTM),
Recurrent Neural Network (RNN), and Transformer models in predicting the stock prices …
Recurrent Neural Network (RNN), and Transformer models in predicting the stock prices …
Deep Learning in Stock Market: Techniques, Purpose, and Challenges
In recent years, deep learning has witnessed a growing interest due to its ability to solve
complex problems and offer accurate results. It has found wide applications in finance …
complex problems and offer accurate results. It has found wide applications in finance …