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Apply big data analytics for forecasting the prices of precious metals futures to construct a hedging strategy for industrial material procurement. (2023). Wu, Chienchang ; Chiu, Kueichen ; Li, Shengtun.
In: Managerial and Decision Economics.
RePEc:wly:mgtdec:v:44:y:2023:i:2:p:942-959.

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  1. Practical forecasting of risk boundaries for industrial metals and critical minerals via statistical machine learning techniques. (2024). Kim, Woo Chang ; Choi, Insu.
    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:94:y:2024:i:c:s1057521924001844.

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  1. Aharon, D. Y., & Qadan, M. (2018). What drives the demand for information in the commodity market? Resources Policy, 59, 532–543. https://doi.org/10.1016/j.resourpol.2018.09.013.

  2. Apergis, N., Christou, C., & Payne, J. E. (2014). Precious metal markets, stock markets and the macroeconomic environment: A FAVAR model approach. Applied Financial Economics, 24(10), 691–703. https://doi.org/10.1080/09603107.2014.899668.

  3. Atsalakis, G., Frantzis, D., & Zopounidis, C. (2016). Commodities' price trend forecasting by a neuro‐fuzzy controller. Energy Systems, 7(1), 73–102. https://doi.org/10.1007/s12667-015-0154-8.
    Paper not yet in RePEc: Add citation now
  4. Bagautdinova, N., Tsaregorodtsev, E., Kulalayeva, I., & Arzhantseva, N. (2014). Assessment of mutual probabilistic influence of volatility of official price for precious metals on the market value of the bi‐currency basket. Mediterranean Journal of Social Sciences, 5(12), 33. https://doi.org/10.5901/mjss.2014.v5n12p33.
    Paper not yet in RePEc: Add citation now
  5. Bildirici, M. E., & Turkmen, C. (2015). Nonlinear causality between oil and precious metals. Resources Policy, 46, 202–211. https://doi.org/10.1016/j.resourpol.2015.09.002.

  6. Charles, A., Darné, O., & Kim, J. H. (2015). Will precious metals shine? A market efficiency perspective. International Review of Financial Analysis, 41, 284–291. https://doi.org/10.1016/j.irfa.2015.01.018.

  7. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427–431.
    Paper not yet in RePEc: Add citation now
  8. Dooley, G., & Lenihan, H. (2005). An assessment of time series methods in metal price forecasting. Resources Policy, 30(3), 208–217. https://doi.org/10.1016/j.resourpol.2005.08.007.

  9. Engle, R. F., & Sheppard, K. (2001). Theoretical and empirical properties of dynamic conditional correlation multivariate GARCH: National Bureau of economic research.

  10. Erdoğdu, A. (2017). The Most significant factors influencing the Price of gold: An empirical analysis of the US market. Economics, 5(5), 399–406.
    Paper not yet in RePEc: Add citation now
  11. Eryiğit, M. (2012). The dynamical relationship between oil price shocks and selected macroeconomic variables in Turkey. Economic Research‐Ekonomska istraživanja, 25(2), 263–276. https://doi.org/10.1080/1331677X.2012.11517507.
    Paper not yet in RePEc: Add citation now
  12. Eryiğit, M. (2017). Short‐term and long‐term relationships between gold prices and precious metal (palladium, silver and platinum) and energy (crude oil and gasoline) prices. Economic Research‐Ekonomska istraživanja, 30(1), 499–510. https://doi.org/10.1080/1331677X.2017.1305778.
    Paper not yet in RePEc: Add citation now
  13. Gaudenzi, B., Pellegrino, R., Zsidisin, G. A., & Bruggi, C. (2019). Foreign exchange risk mitigation strategies in global sourcing: The case of Vortice SPA revisiting supply chain risk (pp. 407–419). Springer.
    Paper not yet in RePEc: Add citation now
  14. Golino, L. (2017). What influences the precious metal market? ModernCoinMart. https://www.moderncoinmart.com/info-vault/articles/what-influences-the-precious-metal-market.html.
    Paper not yet in RePEc: Add citation now
  15. Granger, C. W. (1969). Investigating causal relations by econometric models and cross‐spectral methods. Econometrica: Journal of the Econometric Society, 37, 424–438. https://doi.org/10.2307/1912791.
    Paper not yet in RePEc: Add citation now
  16. Hammoudeh, S., Malik, F., & McAleer, M. (2011). Risk management of precious metals. The Quarterly Review of Economics and Finance, 51(4), 435–441. https://doi.org/10.1016/j.qref.2011.07.002.

  17. Hansen, B. E., & Seo, B. (2002). Testing for two‐regime threshold cointegration in vector error‐correction models. Journal of Econometrics, 110(2), 293–318. https://doi.org/10.1016/S0304-4076(02)00097-0.
    Paper not yet in RePEc: Add citation now
  18. He, K., Chen, Y., & Tso, G. K. (2017). Price forecasting in the precious metal market: A multivariate EMD denoising approach. Resources Policy, 54, 9–24. https://doi.org/10.1016/j.resourpol.2017.08.006.

  19. Hillier, D., Draper, P., & Faff, R. (2006). Do precious metals shine? An Investment Perspective. Financial Analysts Journal, 62, 98–106. https://doi.org/10.2469/faj.v62.n2.4085.
    Paper not yet in RePEc: Add citation now
  20. Kanjilal, K., & Ghosh, S. (2017). Dynamics of crude oil and gold price post 2008 global financial crisis–new evidence from threshold vector error‐correction model. Resources Policy, 52, 358–365. https://doi.org/10.1016/j.resourpol.2017.04.001.
    Paper not yet in RePEc: Add citation now
  21. Karalevicius, V., Degrande, N., & De Weerdt, J. (2018). Using sentiment analysis to predict interday bitcoin price movements. The Journal of Risk Finance, 19(1), 56–75. https://doi.org/10.1108/JRF-06-2017-0092.

  22. Katsiampa, P. (2017). Volatility estimation for bitcoin: A comparison of GARCH models. Economics Letters, 158, 3–6. https://doi.org/10.1016/j.econlet.2017.06.023.

  23. Kucher, O., & McCoskey, S. (2017). The long‐run relationship between precious metal prices and the business cycle. The Quarterly Review of Economics and Finance, 65, 263–275. https://doi.org/10.1016/j.qref.2016.09.005.
    Paper not yet in RePEc: Add citation now
  24. Kumar, S. (2017). On the nonlinear relation between crude oil and gold. Resources Policy, 51, 219–224. https://doi.org/10.1016/j.resourpol.2017.01.003.

  25. Kurucak, A., & Shcherbakova, A. (2016). Estimating the hedging value of an energy exchange in Turkey to a retail power consumer. Energy, 101, 16–26. https://doi.org/10.1016/j.energy.2016.02.005.

  26. Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? Journal of Econometrics, 54(1–3), 159–178. https://doi.org/10.1016/0304-4076(92)90104-Y.

  27. Labys, W. C., Achouch, A., & Terraza, M. (1999). Metal prices and the business cycle. Resources Policy, 25(4), 229–238. https://doi.org/10.1016/S0301-4207(99)00030-6.

  28. Lau, M. C. K., Vigne, S. A., Wang, S., & Yarovaya, L. (2017). Return spillovers between white precious metal ETFs: The role of oil, gold, and global equity. International Review of Financial Analysis, 52, 316–332. https://doi.org/10.1016/j.irfa.2017.04.001.

  29. Li, X., & Wang, C. A. (2017). The technology and economic determinants of cryptocurrency exchange rates: The case of bitcoin. Decision Support Systems, 95, 49–60. https://doi.org/10.1016/j.dss.2016.12.001.
    Paper not yet in RePEc: Add citation now
  30. Lin, C. (2015). Build Prediction Models for Gold Prices Based on Back‐Propagation Neural Network. Paper presented at the 2015 International Conference on Modeling, Simulation and Applied Mathematics.
    Paper not yet in RePEc: Add citation now
  31. Lin, J. Y. (2014). Explore the determinations of price movements for gold and silver. Master thesis of Tunghai University institutional repository, 2014.
    Paper not yet in RePEc: Add citation now
  32. Luo, J., & Chen, X. (2017). Risk hedging via option contracts in a random yield supply chain. Annals of Operations Research, 257(1–2), 697–719. https://doi.org/10.1007/s10479-015-1964-8.

  33. Maamoun, K. (2015). The use of financial hedging in supply chain risk management. Concordia University.
    Paper not yet in RePEc: Add citation now
  34. Mutafoglu, T. H., Tokat, E., & Tokat, H. A. (2012). Forecasting precious metal price movements using trader positions. Resources Policy, 37(3), 273–280. https://doi.org/10.1016/j.resourpol.2012.02.002.

  35. Narayan, P. K., Narayan, S., & Zheng, X. (2010). Gold and oil futures markets: Are markets efficient? Applied Energy, 87(10), 3299–3303. https://doi.org/10.1016/j.apenergy.2010.03.020.

  36. Ng, S., & Perron, P. (2001). Lag length selection and the construction of unit root tests with good size and power. Econometrica, 69(6), 1519–1554. https://doi.org/10.1111/1468-0262.00256.

  37. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. https://doi.org/10.1002/jae.616.

  38. Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. https://doi.org/10.1093/biomet/75.2.335.
    Paper not yet in RePEc: Add citation now
  39. Radetzki, M. (1989). Precious metals: The fundamental determinants of their price behaviour. Resources Policy, 15(3), 194–208. https://doi.org/10.1016/0301-4207(89)90052-4.

  40. Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive‐moving average models of unknown order. Biometrika, 71(3), 599–607. https://doi.org/10.1093/biomet/71.3.599.
    Paper not yet in RePEc: Add citation now
  41. Sari, R., Hammoudeh, S., & Soytas, U. (2010). Dynamics of oil price, precious metal prices, and exchange rate. Energy Economics, 32(2), 351–362. https://doi.org/10.1016/j.eneco.2009.08.010.

  42. Sensoy, A. (2013). Dynamic relationship between precious metals. Resources Policy, 38(4), 504–511. https://doi.org/10.1016/j.resourpol.2013.08.004.

  43. Sharma, S. S. (2016). Can consumer price index predict gold price returns? Economic Modelling, 55, 269–278. https://doi.org/10.1016/j.econmod.2016.02.014.

  44. Sims, C. A. (1980). Macroeconomics and reality. Econometrica: Journal of the Econometric Society, 48, 1–48. https://doi.org/10.2307/1912017.

  45. Soytas, U., Sari, R., Hammoudeh, S., & Hacihasanoglu, E. (2009). World oil prices, precious metal prices and macroeconomy in Turkey. Energy Policy, 37(12), 5557–5566. https://doi.org/10.1016/j.enpol.2009.08.020.

  46. Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250. https://doi.org/10.1016/0304-4076(94)01616-8.

  47. Uddin, G. S., Rahman, M. L., Shahzad, S. J. H., & Rehman, M. U. (2018). Supply and demand driven oil price changes and their non‐linear impact on precious metal returns: A Markov regime switching approach. Energy Economics, 73, 108–121. https://doi.org/10.1016/j.eneco.2018.05.024.

  48. Vigne, S. A., Lucey, B. M., O'Connor, F. A., & Yarovaya, L. (2017). The financial economics of white precious metals—A survey. International Review of Financial Analysis, 52, 292–308. https://doi.org/10.1016/j.irfa.2017.04.006.

  49. Wu, Q., & Chen, A. (2015). Optimal combined purchasing strategies for a risk‐averse manufacturer under price uncertainty. Journal of Industrial Engineering and Management (JIEM), 8(4), 1087–1102. https://doi.org/10.3926/jiem.1289.
    Paper not yet in RePEc: Add citation now
  50. Yelowitz, A., & Wilson, M. (2015). Characteristics of bitcoin users: An analysis of Google search data. Applied Economics Letters, 22(13), 1030–1036. https://doi.org/10.1080/13504851.2014.995359.

  51. Zheng, Y. (2015). The linkage between aggregate investor sentiment and metal futures returns: A nonlinear approach. The Quarterly Review of Economics and Finance, 58, 128–142. https://doi.org/10.1016/j.qref.2015.02.008.

  52. Zhu, X. H., Chen, J.‐Y., & Zhong, M.‐R. (2015). Dynamic interacting relationships among international oil prices, macroeconomic variables and precious metal prices. Transactions of Nonferrous Metals Society of China, 25(2), 669–676. https://doi.org/10.1016/S1003-6326(15)63651-2.
    Paper not yet in RePEc: Add citation now

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    Full description at Econpapers || Download paper

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