An overview of global gold market and gold price forecasting

By Shahriar Shafiee, Erkan Topal. 2010

337 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/ac4ac315a7e50a836b39a4fd4064d14ffb63f145

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. P. Pintelas
2. Nora LAlvarez-Berríos
3. andTMitchell Aide
4. Emmanuel G. Pintelas
5. I. Livieris

Citations in the corpus

• Global demand for gold is another threat for tropical forests (2015, background): “As the global demand and price for gold continues to increase (Shafiee and Topal 2010), gold mining activities will likely continue to increase in the tropical forests of South America.”
• A CNN–LSTM model for gold price time-series forecasting (2020, background): “Shafiee and Topal [27] conducted a comprehensive research in which they briefly presented the chronicles of advances and developments for gold price prediction.”
• Forecasting gold price with the XGBoost algorithm and SHAP interaction values (2021, neutral): “Several studies have confirmed that, because oil still being one of the most popular sources of energy used, crude oil prices are the leading cause of commodity price volatility (Abd Elaziz et al., 2019; He et al., 2010; Lardic & Mignon, 2008; Shafiee & Topal, 2010a, 2010b).”