How Can We Interpret the Estimates of the Full BEKK Model with Asymmetry? The Case of French and German Stock Returns

Tsuji, Chikashi

doi:10.5296/ber.v7i2.12071

Cited by 8 publications

(5 citation statements)

References 10 publications

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“…This paper investigated the effects of structural breaks on stock return volatility persistence by using the US and UK stock market index return data. In economics and finance, GARCH models are highly useful and important as Guo (2017), Tsuji (2014Tsuji ( , 2016bTsuji ( , 2016cTsuji ( , 2017aTsuji ( , 2017bTsuji ( , 2018b, and many other studies demonstrated. Based on this, applying two kinds of GARCH models of standard GARCH and EGARCH models, we derived the following interesting findings.…”

Section: Discussionmentioning

confidence: 99%

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

Tsuji¹

2018

AEF

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This paper quantitatively investigates the effects of structural breaks on stock return volatility persistence by using the US and UK stock market index return data. Applying two kinds of representative univariate GARCH models of standard GARCH and EGARCH models, we derive the following interesting findings. (1) First, we find that for both the US and UK stock market returns, the volatility persistence parameter values of standard GARCH models decrease when structural breaks are taken into account. (2) Second, we further reveal that for both the US and UK stock market returns, the volatility persistence parameter values of EGARCH models again decline when structural breaks are taken into consideration.

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Section: Discussionmentioning

confidence: 99%

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

Tsuji¹

2018

AEF

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“…This paper quantitatively investigated the relations of structural breaks and volatility spillovers by using the stock return data of the US S&P 500 and Canadian Toronto stock exchange composite index. In the fields of business and finance, it is well-known that GARCH approach is highly useful and beneficial as Bollerslev (1986Bollerslev ( , 1990, Nelson (1991), Glosten et al (1993), Engle and Kroner (1995), Tsuji (2016Tsuji ( , 2017aTsuji ( , 2017b, and many other extant studies signified. Based on this, applying the spillover MGARCH models without and with structural break dummy variables, this study derived the following interesting evidence.…”

Section: Summary Implications and Conclusionmentioning

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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“…With regard to the mean equations, a positive A(i,i)A(i,j) and A(i,j) suggest a shock to the ith variable has positive effects on all variable covariances in the next period. Concerning the variance and covariance a positive B(j,j) B(i,j) means an increase in the ith variable has a positive effect on the variables covariances in the next period (Tsuji, 2017). 5-4.18472 0.00000 C(5) -3.71761 0.00000 C(6) 7.016273 0.00000 C(6) -6.71818 0.00710 C 711.67473 0.00000 C 713.24437 0.00000…”

Section: The Estimated Modelmentioning

confidence: 99%

Impact of Shocks on the Balance of Payment Evidence via MGARCH from Sudan

Arabi

2019

International Journal of Applied Economics, Finance and Account

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This research investigates the effects of own shocks on the Sudanese balance of payment (BOP) and shocks from other variables. The model encompasses seven variables that have long-term relationship with each other i.e. ratio of balance of payments to GDP (BOPR), economic growth proxied by per capita GDP (Q), real effective exchange rate (REER), budget deficit ratio to GDP (BUDR), monetization (MNT), inflation rate (INF), and unemployment rate (UR). We use a multivariate generalized autoregressive conditional heteroscedasticity model (MGARVH) for estimation. We chose t distribution because residuals are not multivariate normal. All estimates are highly significant and positive. Positive ARCH effects suggest that a shock to the ith variable has positive effects on all variable covariances in the next period. The multiplication of own shocks by the cross shocks discloses that the covariance of the balance of payments and the inflation rate is the largest contrary to the smallest amount covariance of the balance of payments and the fiscal deficit. The positive estimates of the cross terms capture linkages, the transformation of shocks and volatility spillover effects point toward model variables integration. Covariance stationary test indicates multidirectional volatility spillover runs from single variable to the other variables. Dynamic conditional correlation (DCC) reveals a strong correlation of the variable model comprising both signs. We recommend that policymakers when formulating macroeconomic policies should consider the linkages between these variables taking Kaldor magic square as a guideline. Funding: This study received no specific financial support. Competing Interests: The author declares that there are no conflicts of interests regarding the publication of this paper.

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How Can We Interpret the Estimates of the Full BEKK Model with Asymmetry? The Case of French and German Stock Returns

Cited by 8 publications

References 10 publications

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

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

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

Impact of Shocks on the Balance of Payment Evidence via MGARCH from Sudan

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