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Applied Economics Letters Volume 22, 2015 - Issue 1
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Original Articles

Forecasting gold-price fluctuations: a real-time boosting approach

Christian PierdziochDepartment of Economics, Helmut Schmidt University, 22008Hamburg, GermanyCorrespondence[email protected]
,
Marian RisseDepartment of Economics, Helmut Schmidt University, 22008Hamburg, Germany
&
Sebastian RohloffDepartment of Economics, Helmut Schmidt University, 22008Hamburg, Germany
Pages 46-50 | Published online: 01 Aug 2014

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R. Lehmann & K. Wohlrabe. (2016) Looking into the black box of boosting: the case of Germany. Applied Economics Letters 23:17, pages 1229-1233.
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Christian Pierdzioch, Marian Risse & Sebastian Rohloff. (2016) A boosting approach to forecasting gold and silver returns: economic and statistical forecast evaluation. Applied Economics Letters 23:5, pages 347-352.
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Juan D. Díaz, Erwin Hansen & Gabriel Cabrera. (2023) Gold risk premium estimation with machine learning methods. Journal of Commodity Markets 31, pages 100293.
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Debidutta Pattnaik, M. Kabir Hassan, Arun DSouza & Ali Ashraf. (2023) Investment in gold: A bibliometric review and agenda for future research. Research in International Business and Finance 64, pages 101854.
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Afees A. Salisu, Rangan Gupta, Jacobus Nel & Elie Bouri. (2022) The (Asymmetric) effect of El Niño and La Niña on gold and silver prices in a GVAR model. Resources Policy 78, pages 102897.
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Sujan Reddy A., Akashdeep S., Harshvardhan R.Sowmya Kamath S.. (2022) Stacking Deep learning and Machine learning models for short-term energy consumption forecasting. Advanced Engineering Informatics 52, pages 101542.
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Syed Ali RazaNida ShahMuhammad AliMuhammad Shahbaz. (2021) Do Exchange Rates Fluctuations Influence Gold Price in G7 Countries? New Insights from a Nonparametric Causality-in-Quantiles Test. Zagreb International Review of Economics and Business 24:2, pages 37-57.
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Sami Ben Jabeur, Salma Mefteh-Wali & Jean-Laurent Viviani. (2021) Forecasting gold price with the XGBoost algorithm and SHAP interaction values. Annals of Operations Research.
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Dirk G. Baur, Hubert Dichtl, Wolfgang Drobetz & Viktoria-Sophie Wendt. (2020) Investing in gold – Market timing or buy-and-hold?. International Review of Financial Analysis 71, pages 101281.
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Hubert Dichtl. (2020) Forecasting excess returns of the gold market: Can we learn from stock market predictions?. Journal of Commodity Markets 19, pages 100106.
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Matheus Henrique Dal Molin Ribeiro & Leandro dos Santos Coelho. (2020) Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series. Applied Soft Computing 86, pages 105837.
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Robert Lehmann & Klaus Wohlrabe. (2016) Boosting and regional economic forecasting: the case of Germany. Letters in Spatial and Resource Sciences 10:2, pages 161-175.
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Qingsong Ruan, Ying Huang & Wei Jiang. (2016) The exceedance and cross-correlations between the gold spot and futures markets. Physica A: Statistical Mechanics and its Applications 463, pages 139-151.
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Christian Pierdzioch, Marian Risse & Sebastian Rohloff. (2016) A boosting approach to forecasting the volatility of gold-price fluctuations under flexible loss. Resources Policy 47, pages 95-107.
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Christian Pierdzioch, Marian Risse & Sebastian Rohloff. (2016) A quantile-boosting approach to forecasting gold returns. The North American Journal of Economics and Finance 35, pages 38-55.
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Christian Pierdzioch, Marian Risse & Sebastian Rohloff. (2015) A real-time quantile-regression approach to forecasting gold returns under asymmetric loss. Resources Policy 45, pages 299-306.
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Syed Abul Basher & Perry Sadorsky. (2022) Forecasting Bitcoin Price Direction With Random Forests: How Important Are Interest Rates, Inflation, and Market Volatility?. SSRN Electronic Journal.
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Hubert Dichtl. (2017) Forecasting Excess Returns of the Gold Market: Can We Learn from Stock Market Predictions?. SSRN Electronic Journal.
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Christian Pierdzioch, Marian Risse & Sebastian Rohloff. (2015) Optimists, Pessimists, and the Efficiency of the Gold Market. SSRN Electronic Journal.
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Christian Pierdzioch, Marian Risse & Sebastian Rohloff. (2014) Forecasting the Volatility of Gold-Price Fluctuations. SSRN Electronic Journal.
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