Risk Behavior of Stock Markets Before and After the Subprime Crisis

Thomasz, Esteban Otto; Bariviera, Aurelio F.

doi:10.1007/978-3-642-38279-6_9

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…This recent financial crisis provides a unprecedented opportunity to measure the performance of traditional risk estimators and the different impacts across international markets, such as the EMU stock markets. For instance, developed markets tend to be more stable, and traditional risk measures based on past behavior tend to underestimate risk when a systemic crisis occurs [64].…”

Section: Introductionmentioning

confidence: 99%

A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causality test

Polanco-Martínez

Fernández-Macho

Neumann

et al. 2018

Physica A: Statistical Mechanics and its Applications

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This paper presents an analysis of EU peripheral (so-called PIIGS) stock market indices and the S&P Europe 350 index (SPEURO), as a European benchmark market, over the pre-crisis (2004-2007) and crisis (2008-2011) periods. We computed a rolling-window wavelet correlation for the market returns and applied a non-linear Granger causality test to the wavelet decomposition coefficients of these stock market returns. Our results show that the correlation is stronger for the crisis than for the pre-crisis period. The stock market indices from Portugal, Italy and Spain were more interconnected among themselves during the crisis than with the SPEURO. The stock market from Portugal is the most sensitive and vulnerable PIIGS member, whereas the stock market from Greece tends to move away from the European benchmark market since the 2008 financial crisis till 2011. The non-linear causality test indicates that in the first three wavelet scales (intraweek, weekly and fortnightly) the number of uni-directional and bi-directional causalities is greater during the crisis than in the pre-crisis period, because of financial contagion. Furthermore, the causality analysis shows that the direction of the Granger cause-effect for the pre-crisis and crisis periods is not invariant in the considered timescales , and that the causality directions among the studied stock markets do not seem to have a preferential direction. These results are relevant to better understand the behaviour of vulnerable stock markets, especially for investors and policymakers.

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Section: Introductionmentioning

confidence: 99%

A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causality test

Polanco-Martínez

Fernández-Macho

Neumann

et al. 2018

Physica A: Statistical Mechanics and its Applications

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show abstract

“…For example, Narayan et al (2017) sort equity portfolios into deciles to which labels are given such as Loser portfolio or Winner portfolio. Thomasz and Bariviera (2013) examine the risk behavior of stock markets in 30 countries before and after the sub-prime crisis, and using a variety of risk indicators, they classify markets into high, medium, and low risk. Other authors use techniques such as quantile regression to classify observations into different quantiles according to characteristics such as risk or return (Koenker and Bassett 1978;Allen et al 2009).…”

Section: Ranking Methodologymentioning

confidence: 99%

Do Nonparametric Measures of Extreme Equity Risk Change the Parametric Ordinal Ranking? Evidence from Asia

Powell

Pham

2018

Risks

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There has been much discussion in the literature about how central measures of equity risk such as standard deviation fail to account for extreme tail risk of equities. Similarly, parametric measures of value at risk (VaR) may also fail to account for extreme risk as they assume a normal distribution which is often not the case in practice. Nonparametric measures of extreme risk such as nonparametric VaR and conditional value at risk (CVaR) have often been found to overcome this problem by measuring actual tail risk without applying any predetermined assumptions. However, this article argues that it is not just the actual risk of equites that is important to investor choices, but also the relative (ordinal) risk of equities compared to each other. Using an applied setting of industry portfolios in a variety of Asian countries (benchmarked to the United States), over crisis and non-crisis periods, this article finds that nonparametric measures of VaR and CVaR may provide only limited new information to investors about relative risk in the portfolios examined as there is a high degree of similarity found in relative industry risk when using nonparametric metrics as compared to central or parametric measures such as standard deviation and parametric VaR.

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Risk Behavior of Stock Markets Before and After the Subprime Crisis

Cited by 2 publications

References 8 publications

A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causality test

A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causality test

Do Nonparametric Measures of Extreme Equity Risk Change the Parametric Ordinal Ranking? Evidence from Asia

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