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Prediction of Precious Metal Index Based on Ensemble Learning and SHAP Interpretable Method

Author

Listed:
  • Yanbo Zhang

    (Beijing University of Chemical Technology)

  • Mengkun Liang

    (Beijing University of Chemical Technology)

  • Haiying Ou

    (Beijing Wuzi University)

Abstract

In recent years, the challenging global economy has induced a surge in the investment risk. Precious metal index has gained popularity among investors because of its ability to diversify investments and hedge risk. To facilitate optimal decision-making in the face of market volatility, financial institutions, investors and related enterprises need an efficient and reliable method to predict the price fluctuations of precious metals. Based on these, the primary objective of this study is to develop an ensemble model which could predict precious metal index better. In this study, K-means method is employed for label segmentation, categorizing the price percentage changes of precious metal index into five distinct labels, and four machine learning models are selected for predictive performance comparison: XGBoost, LightGBM, CatBoost, and Random Forests. Then three models with better predictive performance are selected for ensemble. The ensemble model shows improved prediction ability compared to these individual ones and the empirical evidence is provided to demonstrate its robustness. In addition, this study provides an interpretable analysis of the characteristics with the SHAP method and proposes some investment recommendations. These results could provide ideas to the participants in the precious metal market.

Suggested Citation

  • Yanbo Zhang & Mengkun Liang & Haiying Ou, 2024. "Prediction of Precious Metal Index Based on Ensemble Learning and SHAP Interpretable Method," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3243-3278, December.
    • Handle: RePEc:kap:compec:v:64:y:2024:i:6:d:10.1007_s10614-024-10557-w
    DOI: 10.1007/s10614-024-10557-w
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    1. Dirk G. Baur & Brian M. Lucey, 2010. "Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold," The Financial Review, Eastern Finance Association, vol. 45(2), pages 217-229, May.
    2. Irwin, Scott H. & Sanders, Dwight R., 2012. "Financialization and Structural Change in Commodity Futures Markets," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(3), pages 371-396, August.
    3. He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2017. "Price forecasting in the precious metal market: A multivariate EMD denoising approach," Resources Policy, Elsevier, vol. 54(C), pages 9-24.
    4. Sami Ben Jabeur & Salma Mefteh-Wali & Jean-Laurent Viviani, 2021. "Forecasting gold price with the XGBoost algorithm and SHAP interaction values," Post-Print hal-03331805, HAL.
    5. Sun, Xiaolei & Liu, Mingxi & Sima, Zeqian, 2020. "A novel cryptocurrency price trend forecasting model based on LightGBM," Finance Research Letters, Elsevier, vol. 32(C).
    6. Naeem, Muhammad Abubakr & Agyemang, Abraham & Hasan Chowdhury, Md Iftekhar & Hasan, Mudassar & Shahzad, Syed Jawad Hussain, 2022. "Precious metals as hedge and safe haven for African stock markets," Resources Policy, Elsevier, vol. 78(C).
    7. Das, Debojyoti & Bhatia, Vaneet & Kumar, Surya Bhushan & Basu, Sankarshan, 2022. "Do precious metals hedge crude oil volatility jumps?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    8. Qadan, Mahmoud & Aharon, David Y. & Eichel, Ron, 2019. "Seasonal patterns and calendar anomalies in the commodity market for natural resources," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    9. Mensi, Walid & Ali, Syed Riaz Mahmood & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Multiscale dependence, spillovers, and connectedness between precious metals and currency markets: A hedge and safe-haven analysis," Resources Policy, Elsevier, vol. 77(C).
    10. Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2021. "How COVID-19 drives connectedness among commodity and financial markets: Evidence from TVP-VAR and causality-in-quantiles techniques," Resources Policy, Elsevier, vol. 70(C).
    11. Zhang, Ditian & Tang, Pan, 2023. "Forecasting European Union allowances futures: The role of technical indicators," Energy, Elsevier, vol. 270(C).
    12. Zouhaier Dhifaoui & Rabeh Khalfaoui & Mohammad Zoynul Abedin & Baofeng Shi, 2022. "Quantifying information transfer among clean energy, carbon, oil, and precious metals: A novel transfer entropy-based approach," Post-Print hal-03797566, HAL.
    13. Jose Arreola Hernandez & Mazin A.M. Al Janabi, 2020. "Forecasting of dependence, market, and investment risks of a global index portfolio," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 512-532, April.
    14. Rehman, Mobeen Ur & Shahzad, Syed Jawad Hussain & Uddin, Gazi Salah & Hedström, Axel, 2018. "Precious metal returns and oil shocks: A time varying connectedness approach," Resources Policy, Elsevier, vol. 58(C), pages 77-89.
    15. Zhao, Yang & Zhang, Maojun & Pei, Ziting & Nan, Jiangxia, 2023. "The effects of quantitative easing on Bitcoin prices," Finance Research Letters, Elsevier, vol. 57(C).
    16. Yong Shi & Bo Li & Wen Long & Wei Dai, 2022. "Method for Improving the Performance of Technical Analysis Indicators By Neural Network Models," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1027-1068, March.
    17. Li, Ang & Liu, Mark & Sheather, Simon, 2023. "Predicting stock splits using ensemble machine learning and SMOTE oversampling," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    18. Idilbi-Bayaa, Yasmeen & Qadan, Mahmoud, 2022. "What the current yield curve says, and what the future prices of energy do," Resources Policy, Elsevier, vol. 75(C).
    19. Lahiani, Amine & Mefteh-Wali, Salma & Vasbieva, Dinara G., 2021. "The safe-haven property of precious metal commodities in the COVID-19 era," Resources Policy, Elsevier, vol. 74(C).
    20. Wang, Ju-Jie & Wang, Jian-Zhou & Zhang, Zhe-George & Guo, Shu-Po, 2012. "Stock index forecasting based on a hybrid model," Omega, Elsevier, vol. 40(6), pages 758-766.
    21. Lin, Yu & Yan, Yan & Xu, Jiali & Liao, Ying & Ma, Feng, 2021. "Forecasting stock index price using the CEEMDAN-LSTM model," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    22. Peng, Xiaofan, 2020. "Do precious metals act as hedges or safe havens for China's financial markets?," Finance Research Letters, Elsevier, vol. 37(C).
    23. Chi-Wei Su & Kai-Hua Wang & Oana-Ramona Lobonţ & Meng Qin, 2023. "Continuous Wavelet Transform of Time-Frequency Analysis Technique to Capture the Dynamic Hedging Ability of Precious Metals," Mathematics, MDPI, vol. 11(5), pages 1-18, February.
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