Structural Breaks and Volatility Persistence of Stock Returns: Evidence from the US and UK Equity Markets

Tsuji, Chikashi

doi:10.11114/aef.v5i6.3690

Cited by 3 publications

(5 citation statements)

References 17 publications

(20 reference statements)

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“…As a result, they suffer from slow information flow and sluggish absorption of news into the market prices leading to long-term adjustments. Notably, the extremely high volatility persistence levels of close to 1 in China and Russia may suggest significant evidence of structural breaks (Kasman 2009;Tsuji 2018).…”

Section: Variance Equation Resultsmentioning

confidence: 99%

“…On the same market, Goldman and Shen (2018), over the period 2002-2017, reported volatility persistence, asymmetry and a positive risk premium. Tsuji (2018) found that standard GARCH and EGARCH models' volatility persistence parameter values decreased when structural breaks were considered. Thus, failure to consider structural breaks may result in an overestimation of volatility persistence of international stock returns.…”

Section: Literature Reviewmentioning

confidence: 96%

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A Comparative Analysis of the Nature of Stock Return Volatility in BRICS and G7 Markets

Muguto

Muzindutsi

2022

JRFM

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Through globalization and financial market liberalization, the opening up of markets has increased cross-border investments as investors search for higher risk-adjusted returns. This ability to invest internationally has raised the attention given to emerging markets that offer higher risk-adjusted returns relative to developed markets. However, despite the growing importance of emerging markets, the literature on the nature of volatility in global markets is typified by generalizations of findings from developed markets. To fill this gap, this study comparatively examined the nature of stock return volatility in developed G7 and emerging BRICS markets. Broad market index data and GARCH models over the period 2003:01–2020:08 were employed. The study found evidence of volatility persistence, asymmetry, mean reversion and weak evidence of a risk premium in both emerging and developed markets. There was also evidence of significant differences in the nature of volatility within the two sets of markets. These volatility patterns in both groups cast doubt on the assertion that developed markets are more informationally efficient than emerging markets. Thus, markets in the same group may not always have the same nature of volatility, especially in the wake of structural events such as the COVID-19 global pandemic.

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Section: Variance Equation Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 96%

A Comparative Analysis of the Nature of Stock Return Volatility in BRICS and G7 Markets

Muguto

Muzindutsi

2022

JRFM

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“…This paper quantitatively examined the effects of structural breaks in stock returns on their volatility persistence by using the return data of S&P 500 in the US and TOPIX in Japan. In the fields of business, economics, and finance, it is well-known that GARCH models are highly beneficial and important as Bollerslev (1986), Nelson (1991), Engle and Kroner (1995), Tsuji (2016bTsuji ( , 2018d, and numerous other studies suggested. Based on this, applying the diagonal BEKK-MGARCH models with and without structural break dummies, we revealed the following interesting findings.…”

Section: Discussionmentioning

confidence: 99%

A Multivariate Analysis of the Effects of Structural Breaks on Stock Return Volatility Persistence: The Case of the US and Japan

Tsuji¹

2019

IJBA

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This paper quantitatively inspects the effects of structural breaks in stock returns on their volatility persistence by using the stock return data of the US and Japan. More concretely, applying the diagonal BEKK-MGARCH model with and without structural break dummies to the returns of S&P 500 and TOPIX, we reveal the following interesting findings. (1) First, we clarify that for both the US and Japanese stock returns, the values of the GARCH parameters, namely, the values of the volatility persistence parameters in the diagonal BEKK-MGARCH models decrease when we include the structural break dummies in the models. (2) Second, we further find that interestingly, during the Lehman crisis in 2008, the estimated time-varying volatilities from the diagonal BEKK-MGARCH model with structural break dummies are slightly higher than those from the no structural break dummy model. (3) Third, we furthermore reveal that also very interestingly, the estimated time-varying correlations from the diagonal BEKK-MGARCH model with no structural break dummy are slightly higher than those from the structural break dummy model.

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“…Moreover, by applying a new DCC-MEGARCH model, Tsuji (2018c) explored return and volatility transmission between international oil equities and WTI crude oil futures, in which structural break analyses were also conducted for robustness checks. Furthermore, Tsuji (2018aTsuji ( , 2018b also investigated the linkages between stock return structural breaks and their volatility persistence, although the examinations were by univariate analyses.…”

Section: Related Literature Reviewmentioning

confidence: 99%

“…In business and finance literature, structural breaks in time-series stock returns become highly important, and recently, the volatility spillover in international stock markets is also being very important research topic (e.g., Diebold and Yilmaz, 2012;Ewing and Malik, 2016;Tsuji, 2018a;Tsuji, 2018b). Then how are stock return volatility spillovers affected by their structural breaks?…”

Section: Introductionmentioning

confidence: 99%

Structural Breaks and Volatility Spillovers: The Case of the US and Canadian Stock Markets

Tsuji¹

2019

jmr

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This paper investigates the relations of structural breaks and volatility spillovers by using the US and Canadian stock return data. Specifically, applying spillover MGARCH models without and with structural break dummy variables to the two stock returns, this study derives the following interesting evidence. (1) First, we reveal that for both the US and Canadian stock returns, the volatility persistence parameter values in our spillover MGARCH models decline when structural break dummy variables are incorporated. (2) Second, we further clarify that when we do not take structural breaks into account, the spillover effect was unidirectional from Canada to the US. However, when we take structural breaks into consideration, the results from our spillover MGARCH model with structural break dummies demonstrate that the volatility spillover effects between the US and Canada become bidirectional. (3) Third, we furthermore reveal that around the Lehman Brothers bankruptcy in 2008, the time-varying volatilities derived from our spillover MGARCH model with structural break dummy variables show slightly higher values than those volatilities from our spillover MGARCH model with no structural break dummy variable.

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Structural Breaks and Volatility Persistence of Stock Returns: Evidence from the US and UK Equity Markets

Cited by 3 publications

References 17 publications

A Comparative Analysis of the Nature of Stock Return Volatility in BRICS and G7 Markets

A Comparative Analysis of the Nature of Stock Return Volatility in BRICS and G7 Markets

A Multivariate Analysis of the Effects of Structural Breaks on Stock Return Volatility Persistence: The Case of the US and Japan

Structural Breaks and Volatility Spillovers: The Case of the US and Canadian Stock Markets

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