Volatility persistence in the Russian stock market

This paper applies a fractional integration framework to analyse the stochastic behaviour of two Russian stock market volatility indices (namely the originally created RTSVX and the new RVI that has replaced it) using daily data over the period 2010–2018. The empirical findings are consistent and im...

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Detalles Bibliográficos
Autores: Caporale, G.M. (Guglielmo M.)|||/items/9eec80b9-3717-46f0-a5da-1d38cae16ad1, Gil-Alana, L.A. (Luis A.)|||/items/a283ece6-b578-452c-9362-8d1a6255b23c, Tripathy, T. (Trilochan)|||/items/d90294b5-71ee-4f73-b860-b8c9e91a0ee7
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad de Navarra
Repositorio:Dadun. Depósito Académico Digital de la Universidad de Navarra
Idioma:inglés
OAI Identifier:oai:dadun.unav.edu:10171/67131
Acceso en línea:https://hdl.handle.net/10171/67131
Access Level:acceso abierto
Palabra clave:RTSVX
RVI
Volatility
Persistence
Fractional integration
Long memory
Descripción
Sumario:This paper applies a fractional integration framework to analyse the stochastic behaviour of two Russian stock market volatility indices (namely the originally created RTSVX and the new RVI that has replaced it) using daily data over the period 2010–2018. The empirical findings are consistent and imply in all cases that the two series are mean-reverting, i.e. they are not highly persistent and the effects of shocks disappear over time. This is true regardless of whether the errors are assumed to follow a white noise or autocorrelated process; this is confirmed by the rolling window estimation, and it holds for both subsamples, before and after the detected break. On the whole, it seems shocks do not have permanent effects on volatility in the Russian stock market.