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What drives gold returns? A decision tree analysis

Citations

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Cited by:

  1. Atasoy, Özgün & Trudel, Remi & Noseworthy, Theodore J. & Kaufmann, Patrick J., 2022. "Tangibility bias in investment risk judgments," Organizational Behavior and Human Decision Processes, Elsevier, vol. 171(C).
  2. Hoang, Thi-Hong-Van & Wong, Wing-Keung & Zhu, Zhenzhen, 2015. "Is gold different for risk-averse and risk-seeking investors? An empirical analysis of the Shanghai Gold Exchange," Economic Modelling, Elsevier, vol. 50(C), pages 200-211.
  3. Harris, Richard D.F. & Shen, Jian, 2017. "The intrinsic value of gold: An exchange rate-free price index," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 203-217.
  4. Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2024. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 487-513, July.
  5. Werner Kristjanpoller & Kevin Michell & Cristian Llanos & Marcel C. Minutolo, 2025. "Incorporating causal notions to forecasting time series: a case study," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-22, December.
  6. Drachal, Krzysztof, 2019. "Forecasting prices of selected metals with Bayesian data-rich models," Resources Policy, Elsevier, vol. 64(C).
  7. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "Are precious metals a hedge against exchange-rate movements? An empirical exploration using bayesian additive regression trees," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 27-38.
  8. Huang, Xiaoyong & Jia, Fei & Xu, Xiangyun & Yu shi,, 2019. "The threshold effect of market sentiment and inflation expectations on gold price," Resources Policy, Elsevier, vol. 62(C), pages 77-83.
  9. Joscha Beckmann & Theo Berger & Robert Czudaj & Thi-Hong-Van Hoang, 2019. "Tail dependence between gold and sectorial stocks in China: perspectives for portfolio diversification," Empirical Economics, Springer, vol. 56(3), pages 1117-1144, March.
  10. Luo, Xingguo & Qin, Shihua & Ye, Zinan, 2016. "The information content of implied volatility and jumps in forecasting volatility: Evidence from the Shanghai gold futures market," Finance Research Letters, Elsevier, vol. 19(C), pages 105-111.
  11. Rigamonti, Alessandro Paolo & Greco, Giulio & Capocchi, Alessandro, 2024. "Futures, provisional sales, and earnings management in the global gold mining industry," Finance Research Letters, Elsevier, vol. 59(C).
  12. Naeem, Muhammad Abubakr & Qureshi, Fiza & Arif, Muhammad & Balli, Faruk, 2021. "Asymmetric relationship between gold and Islamic stocks in bearish, normal and bullish market conditions," Resources Policy, Elsevier, vol. 72(C).
  13. Hoang, Thi-Hong-Van & Zhu, Zhenzhen & El Khamlichi, Abdelbari & Wong, Wing-Keung, 2019. "Does the Shari’ah screening impact the gold-stock nexus? A sectorial analysis," Resources Policy, Elsevier, vol. 61(C), pages 617-626.
  14. Shahzad, Syed Jawad Hussain & Rahman, Md Lutfur & Lucey, Brian M. & Uddin, Gazi Salah, 2021. "Re-examining the real option characteristics of gold for gold mining companies," Resources Policy, Elsevier, vol. 70(C).
  15. Abdelbari El Khamlichi & Thi Hong Van Hoang & Wing‐keung Wong, 2016. "Is Gold Different for Islamic and Conventional Portfolios? A Sectorial Analysis," Post-Print hal-02964594, HAL.
  16. Plakandaras, Vasilios & Ji, Qiang, 2022. "Intrinsic decompositions in gold forecasting," Journal of Commodity Markets, Elsevier, vol. 28(C).
  17. Döpke, Jörg & Fritsche, Ulrich & Pierdzioch, Christian, 2017. "Predicting recessions with boosted regression trees," International Journal of Forecasting, Elsevier, vol. 33(4), pages 745-759.
  18. Charteris, Ailie & Kallinterakis, Vasileios, 2021. "Feedback trading in retail-dominated assets: Evidence from the gold bullion coin market," International Review of Financial Analysis, Elsevier, vol. 75(C).
  19. I. Sahadudheen & P. K. Santhosh Kumar, 2025. "The Volatility Spillover Between Global Crude Oil and Gold Market: Evidence from Wavelet Coherence and Cross-power Spectrum Models," Computational Economics, Springer;Society for Computational Economics, vol. 66(4), pages 3063-3080, October.
  20. Dichtl, Hubert, 2020. "Forecasting excess returns of the gold market: Can we learn from stock market predictions?," Journal of Commodity Markets, Elsevier, vol. 19(C).
  21. Wu, Wei & Tang, Xiaoping & Lv, Jiake & Yang, Chao & Liu, Hongbin, 2021. "Potential of Bayesian additive regression trees for predicting daily global and diffuse solar radiation in arid and humid areas," Renewable Energy, Elsevier, vol. 177(C), pages 148-163.
  22. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions in Germany With Boosted Regression Trees," Macroeconomics and Finance Series 201505, University of Hamburg, Department of Socioeconomics.
  23. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou, 2021. "Gold Against the Machine," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 5-28, January.
  24. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Karikari, Nana Kwasi & Hammoudeh, Shawkat, 2022. "Time-varying dependence dynamics between international commodity prices and Australian industry stock returns: a Perspective for portfolio diversification," Energy Economics, Elsevier, vol. 108(C).
  25. Ftiti, Zied & Fatnassi, Ibrahim & Tiwari, Aviral Kumar, 2016. "Neoclassical finance, behavioral finance and noise traders: Assessment of gold–oil markets," Finance Research Letters, Elsevier, vol. 17(C), pages 33-40.
  26. Christian Pierdzioch & Marian Risse, 2020. "Forecasting precious metal returns with multivariate random forests," Empirical Economics, Springer, vol. 58(3), pages 1167-1184, March.
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