Development of Russian precious metals sales planning under the conditions of macroeconomic and geopolitical instability

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Abstract

Introduction. Under the influence of external limitations, Russian precious metals market faced new threats and challenges. Metallurgical companies have been forced to re-engineer aff ected business processes. One of the main tasks is to reassess their approach to sales planning. Theoretical analysis. High market volatility triggered by increased macroeconomic and geopolitical risks causes price bubbles. Bubbles have a negative impact on the market because they produce serious deviations from fundamental levels. There is a defi nite connection between negative news and bubbles growth. Empirical analysis. Precious metal prices showed high volatility in 2022. The analysis revealed at least one palladium price bubble formed during March. In the face of increased uncertainty, the main sales objective was to sell as much of the production as possible, which most metallurgical companies have coped with. Results. In order to develop sales planning under constraints, a combined approach is proposed that gives minimal deviations from average prices and reduces bubble probability. It is worth using econometric models for the early identifi cation of price deviations from its fundamentals. It is necessary to encourage the regional trading hubs of precious metals.

About the authors

Ilya Alekseevich Stepanov

National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)

31 Kashirskoe shosse, Moscow 115409, Russia

References

  1. LBMA Precious Metal Prices. URL: https://www.lbma.org.uk/prices-and-data/precious-metal-prices#/ (дата обращения: 30.12.2023).
  2. Smales L. A. News sentiment in the gold futures market // Journal of Banking & Finance. 2014. Vol. 49. P. 275–286. https://doi.org/10.1016/j.jbankfin.2014.09.006
  3. Smales L. A. Asymmetric volatility response to news sentiment in gold futures // Journal of International Financial Markets, Institutions and Money. 2015. Vol. 34. P. 161–172. https://doi.org/10.1016/j.intfin.2014.11.001
  4. Zheng Y. The linkage between aggregate investor sentiment and metal futures returns: A nonlinear approach // The Quarterly Review of Economics and Finance. 2015. Vol. 58. P. 128–142. https://doi.org/10.1016/j.qref.2015.02.008
  5. Stiglitz J. E. Symposium on bubbles // Journal of Economic Perspectives. 1990. Vol. 4, iss. 2. P. 13–18. https://doi.org/10.1257/jep.4.2.13
  6. Shen J., Najand M., Dong F., He W. News and social media emotions in the commodity market // Review of Behavioral Finance. 2017. Vol. 9, iss. 2. P. 148–168. https://doi.org/10.1108/RBF-09-2016-0060
  7. Khalifa A. A., Miao H., Ramchander S. Return distributions and volatility forecasting in metal futures markets: Evidence from gold, silver, and copper // Journal of Futures Markets. 2011. Vol. 31, iss. 1. P. 55–80. https://doi.org/10.1002/fut.20459
  8. Zhao Y., Chang H.-L., Su Ch.-W., Nian R. Gold bubbles: When are they most likely to occur? // Japan and the World Economy. 2015. Vol. 34. P. 17–23. https://doi.org/10.1016/j.japwor.2015.03.001
  9. Khan K., Köseoğlu S. D. Is palladium price in bubble? // Resources Policy. 2020. Vol. 68. Art. 101780. https://doi.org/10.1016/j.resourpol.2020.101780
  10. Maghyereh A., Abdoh H. Can news-based economic sentiment predict bubbles in precious metal markets? // Financial Innovation. 2022. Vol. 8, iss. 1. P. 1–29. https://doi.org/10.1186/s40854-022-00341-w
  11. Gold Return Attribution Model (GRAM). URL: https://www.gold.org/goldhub/tools/gold-return-attributionmodel (дата обращения: 30.12.2023).

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