Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM

Forecasting Crude Oil Prices Using Ensemble Empirical Mode Decomposition and Sparse Bayesian Learning

(2018) Taiyong Li et al.   Energies

Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models

(2018) Ha Young Kim et al.   EXPERT SYSTEMS WITH APPLICATIONS

Energy Commodity Price Forecasting with Deep Multiple Kernel Learning

(2018) Shian-Chang Huang et al.   Energies

The chaotic behavior among the oil prices, expectation of investors and stock returns: TAR-TR-GARCH copula and TAR-TR-TGARCH copula

(2018) Melike Bildirici   Petroleum Science

Volatility of main metals forecasted by a hybrid ANN-GARCH model with regressors

(2017) Werner Kristjanpoller R et al.   EXPERT SYSTEMS WITH APPLICATIONS

A study on chaos in crude oil markets before and after 2008 international financial crisis

(2017) Salim Lahmiri   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

Forecasting volatility in oil prices with a class of nonlinear volatility models: smooth transition RBF and MLP neural networks augmented GARCH approach

(2015) Melike Bildirici et al.   Petroleum Science

Forecasting oil prices: Smooth transition and neural network augmented GARCH family models

(2013) Melike Bildirici et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Improving forecasts of GARCH family models with the artificial neural networks: An application to the daily returns in Istanbul Stock Exchange

(2008) Melike Bildirici et al.   EXPERT SYSTEMS WITH APPLICATIONS