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Applied Economics Letters Volume 23, 2016 - Issue 5
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Original Articles

A boosting approach to forecasting gold and silver returns: economic and statistical forecast evaluation

Christian PierdziochDepartment of Economics, Helmut Schmidt University, Hamburg, GermanyCorrespondence[email protected]
,
Marian RisseDepartment of Economics, Helmut Schmidt University, Hamburg, Germany
&
Sebastian RohloffDepartment of Economics, Helmut Schmidt University, Hamburg, Germany
Pages 347-352 | Published online: 03 Aug 2015

Citations (16)

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Read on this site (3)

Minghuan Shou, Xueqi Bao & Jie Yu. (2023) An optimal weighted machine learning model for detecting financial fraud. Applied Economics Letters 30:4, pages 410-415.
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Christian Pierdzioch, Monique B. Reid & Rangan Gupta. (2018) On the directional accuracy of inflation forecasts: evidence from South African survey data. Journal of Applied Statistics 45:5, pages 884-900.
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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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Articles from other publishers (13)

OlaOluwa S. Yaya, Adewale F. Lukman & Xuan Vinh Vo. (2022) Persistence and volatility spillovers of bitcoin price to gold and silver prices. Resources Policy 79, pages 103011.
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Juan D. Díaz, Erwin Hansen & Gabriel Cabrera. (2022) Gold risk premium estimation with machine learning methods. Journal of Commodity Markets, pages 100293.
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Vasilios Plakandaras, Periklis Gogas & Theophilos Papadimitriou. (2020) Gold Against the Machine. Computational Economics 57:1, pages 5-28.
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Afees A. Salisu, Umar B. Ndako & Tirimisiyu F. Oloko. (2019) Assessing the inflation hedging of gold and palladium in OECD countries. Resources Policy 62, pages 357-377.
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Neil A. Wilmot. (2019) Heavy Metals: Might as Well Jump. International Journal of Financial Studies 7:2, pages 33.
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Marian Risse. (2019) Combining wavelet decomposition with machine learning to forecast gold returns. International Journal of Forecasting 35:2, pages 601-615.
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Guo-Dong Liu & Chi-Wei Su. (2019) The dynamic causality between gold and silver prices in China market: A rolling window bootstrap approach. Finance Research Letters 28, pages 101-106.
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Marian Risse & Ludwig Ohl. (2017) Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market. Journal of Empirical Finance 44, pages 158-176.
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Samuel A. Vigne, Brian M. Lucey, Fergal A. O’Connor & Larisa Yarovaya. (2017) The financial economics of white precious metals — A survey. International Review of Financial Analysis 52, pages 292-308.
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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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Marian Risse. (2017) Combining Wavelet Decomposition with Machine Learning to Forecast Gold Returns. SSRN Electronic Journal.
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Marian Risse. (2016) Using Dynamic Model Averaging in State Space Representation with Dynamic Occam's Window and Applications to the Stock and Gold Market. SSRN Electronic Journal.
Crossref
Christian Pierdzioch, Marian Risse & Sebastian Rohloff. (2014) Forecasting the Volatility of Gold-Price Fluctuations. SSRN Electronic Journal.
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