The dynamics of volatility spillovers among Russian economy sectors

Volatility is an indicator of the risk existing in the economy, and its volume characterizes the magnitude of risks transmitted from one sector to another. The objective of the study is to determine the dynamics of volatility spillovers among sectors of the Russian economy during crisis periods and classify sectors into shock transmitters and shock receivers. The daily returns of the Moscow Exchange sector indices for 2018-2023 acted as data. The Diebold-Yilmaz methodology based on the VAR model is used to determine the dynamics of volatility spillovers. The study has revealed that the nature of volatility spillovers differs in the pre-crisis period, during the COVID-19 pandemic, and during the special military operation (SMO). The financial sector is a source of volatility spillovers in the first and the last periods. During the pandemic, the oil and gas and transport sectors become volatility receivers. During the period of the SMO, the metallurgy and petrochemical sectors act as receivers of volatility spillovers, while the consumer goods and financial sectors act as their sources.

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Publication Details

Journal
Voprosy Ekonomiki
Published
2024-12-04
DOI
https://doi.org/10.32609/0042-8736-2024-12-50-68
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
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article

The dynamics of volatility spillovers among Russian economy sectors

A. G. Mirzoyan, Yu. V. Kudryavtseva
Voprosy Ekonomiki
Market Dynamics and Volatility
article

The dynamics of volatility spillovers among Russian economy sectors

A. G. Mirzoyan, Yu. V. Kudryavtseva
article en

Abstract

Volatility is an indicator of the risk existing in the economy, and its volume characterizes the magnitude of risks transmitted from one sector to another. The objective of the study is to determine the dynamics of volatility spillovers among sectors of the Russian economy during crisis periods and classify sectors into shock transmitters and shock receivers. The daily returns of the Moscow Exchange sector indices for 2018-2023 acted as data. The Diebold-Yilmaz methodology based on the VAR model is used to determine the dynamics of volatility spillovers. The study has revealed that the nature of volatility spillovers differs in the pre-crisis period, during the COVID-19 pandemic, and during the special military operation (SMO). The financial sector is a source of volatility spillovers in the first and the last periods. During the pandemic, the oil and gas and transport sectors become volatility receivers. During the period of the SMO, the metallurgy and petrochemical sectors act as receivers of volatility spillovers, while the consumer goods and financial sectors act as their sources.

Voprosy Ekonomiki(12)
Lomonosov Moscow State University (RU), Central Bank of the Russian Federation (RU), Moscow State University (TJ)
Openalex Percentile: Top 73%
Market Dynamics and Volatility
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