Equity Risk and Return across Hidden Market Regimes

The key to understanding the dynamics of stock markets, particularly the mechanisms of their changes, is in the concept of the market regime. It is regarded as a regular transition from one state to another. Although the market agenda is never the same, its functioning regime allows us to reveal the...

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Autores principales:	Dmitry A. Endovitsky, Viacheslav V. Korotkikh, Denis A. Khripushin
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	correlation surprise financial turbulence Mahalanobis distance hidden regimes of stock markets Insurance HG8011-9999
Acceso en línea:	https://doaj.org/article/3988d03430634c5ebb43520d41e058d6
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spelling	oai:doaj.org-article:3988d03430634c5ebb43520d41e058d62021-11-25T18:56:04ZEquity Risk and Return across Hidden Market Regimes10.3390/risks91101882227-9091https://doaj.org/article/3988d03430634c5ebb43520d41e058d62021-10-01T00:00:00Zhttps://www.mdpi.com/2227-9091/9/11/188https://doaj.org/toc/2227-9091The key to understanding the dynamics of stock markets, particularly the mechanisms of their changes, is in the concept of the market regime. It is regarded as a regular transition from one state to another. Although the market agenda is never the same, its functioning regime allows us to reveal the logic of its development. The article employs the concept of financial turbulence to identify hidden market regimes. These are revealed through the ratio of the components, which describe single changes of correlated risks and volatility. The combinations of typical and atypical variates of correlational and magnitude components of financial turbulence allowed four hidden regimes to be revealed. These were arranged by the degree of financial turbulence, conceptually analyzed and assessed from the perspective of their duration. The empirical data demonstrated ETF day trading profits for S&P 500 sectors, covering the period of January 1998–August 2020, as well as day trade profits of the Russian blue chips within the period of October 2006–February 2021. The results show a significant difference in regard to the market performance and volatility, which depend on hidden regimes. Both sample data groups demonstrated similar contemporaneous and lagged effects, which allows the prediction of volatility jumps in the periods following atypical correlations.Dmitry A. EndovitskyViacheslav V. KorotkikhDenis A. KhripushinMDPI AGarticlecorrelation surprisefinancial turbulenceMahalanobis distancehidden regimes of stock marketsInsuranceHG8011-9999ENRisks, Vol 9, Iss 188, p 188 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	correlation surprise financial turbulence Mahalanobis distance hidden regimes of stock markets Insurance HG8011-9999
spellingShingle	correlation surprise financial turbulence Mahalanobis distance hidden regimes of stock markets Insurance HG8011-9999 Dmitry A. Endovitsky Viacheslav V. Korotkikh Denis A. Khripushin Equity Risk and Return across Hidden Market Regimes
description	The key to understanding the dynamics of stock markets, particularly the mechanisms of their changes, is in the concept of the market regime. It is regarded as a regular transition from one state to another. Although the market agenda is never the same, its functioning regime allows us to reveal the logic of its development. The article employs the concept of financial turbulence to identify hidden market regimes. These are revealed through the ratio of the components, which describe single changes of correlated risks and volatility. The combinations of typical and atypical variates of correlational and magnitude components of financial turbulence allowed four hidden regimes to be revealed. These were arranged by the degree of financial turbulence, conceptually analyzed and assessed from the perspective of their duration. The empirical data demonstrated ETF day trading profits for S&P 500 sectors, covering the period of January 1998–August 2020, as well as day trade profits of the Russian blue chips within the period of October 2006–February 2021. The results show a significant difference in regard to the market performance and volatility, which depend on hidden regimes. Both sample data groups demonstrated similar contemporaneous and lagged effects, which allows the prediction of volatility jumps in the periods following atypical correlations.
format	article
author	Dmitry A. Endovitsky Viacheslav V. Korotkikh Denis A. Khripushin
author_facet	Dmitry A. Endovitsky Viacheslav V. Korotkikh Denis A. Khripushin
author_sort	Dmitry A. Endovitsky
title	Equity Risk and Return across Hidden Market Regimes
title_short	Equity Risk and Return across Hidden Market Regimes
title_full	Equity Risk and Return across Hidden Market Regimes
title_fullStr	Equity Risk and Return across Hidden Market Regimes
title_full_unstemmed	Equity Risk and Return across Hidden Market Regimes
title_sort	equity risk and return across hidden market regimes
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3988d03430634c5ebb43520d41e058d6
work_keys_str_mv	AT dmitryaendovitsky equityriskandreturnacrosshiddenmarketregimes AT viacheslavvkorotkikh equityriskandreturnacrosshiddenmarketregimes AT denisakhripushin equityriskandreturnacrosshiddenmarketregimes
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Equity Risk and Return across Hidden Market Regimes

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