Financial market interdependencies: A quantile regression analysis of volatility spillover

Rejeb, Aymen Ben; Arfaoui, Mongi

doi:10.1016/j.ribaf.2015.09.022

Cited by 66 publications

(36 citation statements)

References 69 publications

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“…This fact indicated that the effects of shocks and lagged volatility persistence resulting from the market itself presented greater magnitude than those resulting from other markets, whether for the Latin American markets, or for the developed ones. This ascertainment is in accordance to what was detected by Rejeb & Arfaoui (2016).…”

Section: Interdependence Phenomenon and Asymmetriessupporting

confidence: 92%

“…Several empirical studies also found similar results, such as those by Rejeb & Arfaoui (2016) and Valenzuela & Rodríguez (2015). The reason is that, for all the index pairs, a shock occurred in the t-1 returns of a market tends to increase the volatility of another one in t. Moreover, the conditional volatility of a certain index depends on past conditional volatilities of others.…”

Section: Interdependence Phenomenon and Asymmetriessupporting

confidence: 70%

See 1 more Smart Citation

Interdependence and asymmetries: Latin American ADRs and developed markets

Corrêa¹,

Júnior²,

Gaio³

2018

BBR

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Section: Interdependence Phenomenon and Asymmetriessupporting

confidence: 92%

Section: Interdependence Phenomenon and Asymmetriessupporting

confidence: 70%

Interdependence and asymmetries: Latin American ADRs and developed markets

Corrêa¹,

Júnior²,

Gaio³

2018

BBR

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“…On the one hand, by running the model in a long span of time, 1993-2013, we are able to test the decoupling hypothesis, measuring the evolution of volatility transmission and conditional correlation between US and Mexico and Brazil, the two largest markets in the region. On the other hand, to our knowledge, this is the first study that tests volatility transmissions between US and Latin American stock markets using the MGARCH-BEKK model, unlike previous studies (Christofi and Pericli, 1999;Edwards and Susmel, 2001;Weber, 2012;Rejeb and Arfaoui, 2015). The MGARCH-BEKK model is currently deemed as the standard methodology for detecting volatility spillovers amongst financial markets (Gannon and Au-Yeung 2004;Caporale, Pittis and Spagnolo, 2006;Koulakiotis, Dasilas and Papasyriopoulos, 2009;Hammoudeh, Yuan, McAleer and Thompson, 2010;Fayyad and Daly, 2011;Arouri, Jouini and Nguyen, 2011;Andreou, Matsi, and Savvides, 2013).…”

Section: Introductionmentioning

confidence: 93%

“…A wide set of studies have explored volatility transmission between stock markets. For example, Lin, Engle and Ito (1994) Rejeb and Arfaoui, (2015), who study interdependence between the stock markets of US and Japan and a set of emerging stock markets, including five of Latin America, interpreting their results as an indirect evidence of volatility transmission.…”

Section: Introductionmentioning

confidence: 99%

Volatility transmission between US and Latin American stock markets: Testing the decoupling hypothesis

Cardona

Gutiérrez

Agudelo

2017

Research in International Business and Finance

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We test for volatility transmission between US and the six largest Latin American stock markets (Argentina, Brazil, Chile, Colombia, Mexico and Peru) using MGARCH-BEKK models in daily frequency from March 1993 to March 2013. As expected, we find strong evidence of volatility transmission from US to the Latin American markets but not so in the opposite direction. Testing the hypothesis of decoupling between US and Brazil and Mexico the evidence goes against it: the conditional correlations between US and the two emerging markets have steadily increased over the sample period and the volatility transmission have become more significant from 2003 onwards. We also find some evidence on the leadership of Brazil in the region, being the only Latin American stock market consistently transmitting volatility to US.

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“…In addition to these indices, we have considered the volatility of oil prices and the volatility of the EUSTOXX European market. In this paper, we have used a quantile regression method (Engle and Manganelli, 2004;Alexander, 2008;Birău and Antonescu, 2014;Naifar, 2016;Aymen and Mongi, 2016) to analyze the impact of uncertainty on major European market indices. Precisely, we propose a new model based on quantitative regression approach to explore how the individual mentioned risk factors affect the returns and volatility of the market index DAX and the FTSE 100.…”

mentioning

confidence: 99%

Impact of Uncertainty on European Market Indices Quantile Regression Approach

Bohdalová

Greguš

2017

CBUP

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Contemporary Europe needs to make important collective economic and foreign-policy decisions. Many authors argue that uncertainty has influence on the markets' behavior. Therefore, we have decided to analyze the impact of the uncertainty on the returns and the volatility of two major European market indices Germany (DAX) and the U.K. (FTSE 100) across selected quantiles. We present results for the time-period from January 3, 2000 to December 30, 2016. As influential factors, we consider the Economic policy uncertainty (EPU) indices for Europe, the United Kingdom, Brexit and low prices of the crude oil. In our paper, we have found an asymmetric dependence of the analyzed market indices on the selected factors. EPU Brexit had no or weak impact on the analyzed data. Our conclusion shows to investors how sensitive German and English markets are to the uncertainty in Europe. JEL Classification Numbers: C21, C40, G11; DOI: http://dx.doi.org/10.12955/cbup.v5.902 Keywords: quantile regression, uncertainty, Brexit. IntroductionPolicy uncertainty in Europe has intensified because of the Global Financial Crisis, serial crises in the Eurozone, Brexit, etc. Following the recession in 2007-2009, the uncertainty of economic policy has increased as a result of uncertainty among businesses and households about future tax, regulatory, spending, health and monetary policies. However, dominant entrepreneurs and households decreased their spending on investment, consumption and rent following the recession, which resulted in slowing down the increase in policy uncertainty. Baker et al. (2015) investigated the role of policy uncertainty, and they have developed an index of economic uncertainty (EPU) for the United States. Bloomberg gives us an opportunity to analyze economic policy uncertainty for Europe, the United Kingdom and for Brexit in indices EPUCCEUM, EPUCUK, and EPUCBREX. The construction of these indices is based on newspaper articles regarding policy uncertainty concerning economy, uncertainty and information on spending, deficit, regulation, budget, tax, policy, or the Bank of England, or the ECB. We have taken EPU indices as risk factors for analyzing two major European markets -the DAX, Germany market and the FTSE 100, UK market. In addition to these indices, we have considered the volatility of oil prices and the volatility of the EUSTOXX European market. In this paper, we have used a quantile regression method (Engle and Manganelli, 2004;Alexander, 2008;Birău and Antonescu, 2014;Naifar, 2016;Aymen and Mongi, 2016) to analyze the impact of uncertainty on major European market indices. Precisely, we propose a new model based on quantitative regression approach to explore how the individual mentioned risk factors affect the returns and volatility of the market index DAX and the FTSE 100. Our quantile regression model enables us to analyze the dynamics of the co-movement of the returns and volatilities through selected quantiles. Our findings give insight into the reaction of European equity markets to uncertain...

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Financial market interdependencies: A quantile regression analysis of volatility spillover

Cited by 66 publications

References 69 publications

Interdependence and asymmetries: Latin American ADRs and developed markets

Interdependence and asymmetries: Latin American ADRs and developed markets

Volatility transmission between US and Latin American stock markets: Testing the decoupling hypothesis

Impact of Uncertainty on European Market Indices Quantile Regression Approach

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