Author(s): Alicia Estefania Antonio Figueroa

This work implements deep learning models to capture non-linear and complex data behavior in aluminum price data. Deep learning models include the long short-term memory (LSTM) and deep feedforward neural networks (FFNN). The support vector regression (SVR) is employed as a base model for comparison. Each predictive model is tuned by using two different o ...

Article GUID: 41751647

Author(s): Roozbeh Nia A; Awasthi A; Bhuiyan N;

Within an uncertain environment and following carbon trade policies, this study uses the Extended Exergy Accounting (EEA) method for coal supply chains (SCs) in eight of the world's most significant coal consuming countries. The purpose is to improve the sustainability of coal SCs in terms of Joules rather than money while considering economic, enviro ...

Article GUID: 37363701

Author(s): Aktas OU; Kryzanowski L; Zhang J;

The intraday volatility effects of price-limit hits for stocks in the BIST-50 index during a volatile period are examined. Our evidence supports the volatility no-effect, dampening and spillover hypotheses depending on whether the lower or upper price limit is hit and on when the hit begins and ends. Post-hit volatilities tend to be lower for limit hits n ...

Article GUID: 32837364

Author(s): Huq I, Nargis N, Lkhagvasuren D, Hussain AG, Fong GT

Tob Control. 2019 05;28(Suppl 1):s37-s44 Authors: Huq I, Nargis N, Lkhagvasuren D, Hussain AG, Fong GT

Article GUID: 29695459