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Shocks propagation mechanism analysis on Russian commodity exchanges: The example of The Moscow Exchange

Author

Listed:
  • Tina Rakic

    (Saint Petersburg State University, Saint Petersburg, Russian Federation)

  • Lyudmila Gadasina

    (Saint Petersburg State University, Saint Petersburg, Russian Federation)

Abstract

Events over the past twenty years have demonstrated that the largest crises have been provoked by external shocks, with financial and commodity markets playing a significant role in their spread. This paper aims to identify and describe the shock propagation mechanism using the example of the Moscow Exchange commodity market. This study explores the time series volatility of commodity futures contracts for the period from January 2021 to February 2025. This work implements a new approach to time series analysis — Connectedness Approach based on the TVP-VAR model. This study contributes to the expansion of research on the analysis of shock propagation mechanisms in Russian financial markets in two ways: by applying a methodology for assessing connectivity and by analyzing data from the commodity market on the Moscow Exchange. The paper shows that oil is a source of changes in the commodity market. It is shown that oil is a source of changes that are passed on to precious metals. During the period under review, gas remained relatively independent of other commodities. The results obtained can be used by investors when forming a securities portfolio, businesses to develop financial management strategies, or exchange institutions in making regulatory decisions.

Suggested Citation

  • Tina Rakic & Lyudmila Gadasina, 2026. "Shocks propagation mechanism analysis on Russian commodity exchanges: The example of The Moscow Exchange," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 81, pages 46-67.
    • Handle: RePEc:ris:apltrx:022381
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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