Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone

Anagnostidis, Panagiotis; Varsakelis, Christos; Emmanouilides, Christos J.

doi:10.1016/j.physa.2015.12.017

Cited by 109 publications

(65 citation statements)

References 47 publications

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“…The stock and commodity markets were in particular peril as they exhibit a long-range dependence (Lahmiri [7]). However, the impact of the GFC was not limited only to stock markets of large economies as the Eurozone (Anagnostidis et al [8]), the U.S. (Chen et al [3]), or China (Yang et al [9]; Chen et al [3]) but it also spread to relatively smaller, yet important, economies in Asia (Yim et al [10]; Kantar et al [11]; Nobi et al [12]; Hui and Chen [13]; Kuzubaş et al [14]; Kanjamapornkul et al [15]), Africa (Majapa and Gossel [16]) and Latin America (Güloğlu et al [17]). …”

Section: Introduction: Motivation Related Literature and Contributionmentioning

confidence: 99%

Networks of volatility spillovers among stock markets

Baumöhl

Kočenda

Lyócsa

et al. 2018

Physica A: Statistical Mechanics and its Applications

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. We show significant temporal proximity effects between markets and somewhat weaker temporal effects with regard to the US equity marketvolatility spillovers decrease when markets are characterized by greater temporal proximity. Terms of use: Documents inVolatility spillovers also present a high degree of interconnectedness. Our results also link spillovers of escalating magnitude with increasing market size, market liquidity and economic openness.JEL-Codes: C310, C580, F010, G010, G150.Keywords: volatility spillovers, stock markets, shock transmission, Granger causality network, spatial regression, financial crisis. We benefited from helpful comments we received from two anonymous referees and participants at several presentations. Eduard Baumöhl University of Economics in Bratislava

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Section: Introduction: Motivation Related Literature and Contributionmentioning

confidence: 99%

Networks of volatility spillovers among stock markets

Baumöhl

Kočenda

Lyócsa

et al. 2018

Physica A: Statistical Mechanics and its Applications

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“…Although DFA was created to study the behaviour of DNA [19], it was extended to study other phenomena, including the behaviour of financial series. Studies such as Ferreira and Dionísio [9], Kristoufek [20], Cao and Zhang [21] or Anagnostidis et al [22] are just some examples of relatively recent studies that analyse stock markets using DFA, and also find common evidence of long-term dependence.…”

Section: Serial Dependence In Stock Markets: a Brief Reviewmentioning

confidence: 99%

Non-linear dependencies in African stock markets: Was subprime crisis an important factor?

Ferreira

Dionísio

Correia

2018

Physica A: Statistical Mechanics and its Applications

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h i g h l i g h t s• It is applied the DFA to analyse the behaviour of 12 African stock indices.• The results point to the existence of statistically significant serial dependence.• Dependence is higher in African stock markets, when compared with other indices. a b s t r a c tThe historical dependence in stock markets it is a very explored issue, especially in developed markets. In this paper we try to address the question of global dependency in African stock markets, and for that purpose we use a global approach able to capture the long-term dependencies being linear or non-linear ones. Are there significant differences in terms of results compared to the major international markets? Results point to an affirmative answer. The Hurst exponent shows that long-term dependence is probably linked not only to size or liquidity.

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“…For example, Liu et al (1997) found persistent volatility in the S&P 500, and Ausloos et al (1999) and Ausloos (2000) found evidence of long-term dependence in exchange markets. In terms of studies specifically examining stock markets -and using only more recent examples -Ferreira and Dionísio (2014), Kristoufek (2015), Cao and Zhang (2015), and Anagnostidis et al (2016) also found evidence of dependence. It should be noted, however, that the main objective of our paper is not an in-depth literature review of EMH once we analyze the specific behavior of Apple, Alphabet, and Microsoft shares; for a more complete survey of EMH, see Sewell (2011).…”

Section: Brief Analysis Of the Efficient Market Hypothesismentioning

confidence: 99%

Apple, Alphabet or Microsoft: Which Is the Most Efficient Share?

Ferreira

2016

ERFIN

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The study of efficiency of financial assets remains important because the non-observation of this feature could mean that investors could have some capacity of predict the behavior of that asset. In this paper we use detrended fluctuation analysis to analyse the efficiency of the three most valuable American companies, curiously all from the same economic sector: Apple, Alphabet and Microsoft. Results point to efficiency of Apple’s shares and similar results for Alphabet. Just Microsoft has shares which show evidence of deviations from the efficiency. Our results also suggest that moments of crisis could have impact on changes in the efficiency patter of shares.

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Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone

Cited by 109 publications

References 47 publications

Networks of volatility spillovers among stock markets

Networks of volatility spillovers among stock markets

Non-linear dependencies in African stock markets: Was subprime crisis an important factor?

Apple, Alphabet or Microsoft: Which Is the Most Efficient Share?

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