Modelling stock volatilities during financial crises: A time varying coefficient approach

Karanasos, Menelaos; Paraskevopoulos, Alexandros G.; Ali, Faek Menla; Karoglou, Michail; Yfanti, Stavroula

doi:10.1016/j.jempfin.2014.08.002

Cited by 29 publications

(25 citation statements)

References 28 publications

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“…Given the macroeconomic slowdown and the widespread fear of an international systemic …nancial collapse, an interesting issue is whether the main stochastic properties of the underlying …nancial time series of these markets and their cross-shock and volatility spillovers have been a¤ected by the crisis. Karanasos et al (2014) do indeed …nd a time varying pattern in the persistence of the volatility of stock market returns, as well as their correlations, cross-shock and volatility spillovers during the period. Surprisingly, the aforementioned impact in relation to the commodity futures markets has drawn less attention.…”

Section: Introductionmentioning

confidence: 74%

“…More speci…cally, we use a battery of tests to identify the number and estimate the timing of breaks, both in the mean and volatility dynamics. Then, we use these breaks in the univariate context, by adopting an asymmetric generalised autoregressive conditional heteroscedasticity (AGARCH) model, to determine changes in the volatility persistence and in the multivariate one, by employing the recently developed unrestricted extended dynamic conditional correlation (UEDCC) AGARCH model of Karanasos et al (2014), to analyse the volatility transmission and the correlation structure. It follows that the adopted univariate and multivariate frameworks are completely time-varying, and more strikingly, unlike the methods used in the existing literature the adopted bivariate model is su¢ ciently ‡exible and allows for volatility spillovers of either positive or negative sign.…”

Section: Introductionmentioning

confidence: 99%

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Modelling time varying volatility spillovers and conditional correlations across commodity metal futures

Karanasos

Ali

Margaronis

et al. 2018

International Review of Financial Analysis

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This paper examines how the most prevalent stochastic properties of key metal futures returns have been a¤ected by the recent …nancial crisis using both mapped and unmapped data. Our results suggest that copper and gold futures returns exhibit time varying persistence in their corresponding conditional volatilities over the crisis period; in particular, such persistence increases during periods of high volatility compared with low volatility. The estimation of a bivariate GARCH model further shows the existence of time varying volatility spillovers between these returns during the di¤erent stages of such a crisis. Our results, which are broadly the same in relation to the use of mapped or unmapped data, suggest that the volatilities of copper and gold are inherently linked, although these metals have very di¤erent applications.

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Section: Introductionmentioning

confidence: 74%

Section: Introductionmentioning

confidence: 99%

Modelling time varying volatility spillovers and conditional correlations across commodity metal futures

Karanasos

Ali

Margaronis

et al. 2018

International Review of Financial Analysis

Self Cite

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“…The existence of structural breaks is a classical statistical problem which affects volatility and long-range dependence in stock returns (Andreou & Chysels, 2002). Besides cointegration literature, the test on structural breaks has been actively used in analyses of volatility spillovers, more specifically for investigation of the contagion phenomenon and for identification of the length of the financial crisis (e.g., Karanasos et al, 2014;Dimitriou, Kenourgios & Simos, 2013). A structural break, which can naturally be associated with the crisis shock, may change the stock market interdependencies during the crisis.…”

Section: Cointegrationmentioning

confidence: 99%

Asymmetry in spillover effects: Evidence for international stock index futures markets

Yarovaya

Brzeszczyński

Lau

2017

International Review of Financial Analysis

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The paper investigates the asymmetry in return and volatility spillovers across futures markets with non-overlapping stock exchange trading hours. The transmission of positive and negative return and volatility shocks is analysed for 104 channels of information conveyance identified by combining 9 developed and 11 emerging markets in markets pairs with nonoverlapping trading hours. The asymmetric causality test is employed to daily stock index futures returns and volatilities for the period from 03 October 2010 to 03 October 2014. The paper sheds the light on the relatively little explored concept of asymmetry in return and volatility spillovers across markets, providing the novel evidence on stabilizing and destabilizing spillover effects.

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“…At the same time, many studies focus on the impact of financial crises on the volatility spillover. A recent study by Karanasos et al (2014) points out that volatility persistence and volatility spillovers in stock market returns show significant time variation. The authors find breaks in variance for all series connected to main economic events with global impact.…”

Section: Introductionmentioning

confidence: 99%

Volatility Transmission across Financial Markets: A Semiparametric Analysis

Kolaiti

Mboya

Sibbertsen

2020

JRFM

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This paper revisits the question whether volatilities of different markets and trading zones have a long-run equilibrium in the sense that they are fractionally cointegrated. We consider the U.S., Japanese and German stock, bond and foreign exchange markets to see whether there is fractional cointegration between the markets in one trading zone or for one market across trading zones. Also the other combinations of different markets in different trading zones are considered. Applying a purely semiparametric approach through the whole analysis shows fractional cointegration can only be found for a small minority of different cases. Investigating further we find that all volatility series show persistence breaks during the observation period which may be a reason for different findings in previous studies.

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Modelling stock volatilities during financial crises: A time varying coefficient approach

Cited by 29 publications

References 28 publications

Modelling time varying volatility spillovers and conditional correlations across commodity metal futures

Modelling time varying volatility spillovers and conditional correlations across commodity metal futures

Asymmetry in spillover effects: Evidence for international stock index futures markets

Volatility Transmission across Financial Markets: A Semiparametric Analysis

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