Asymmetric dependence patterns in financial time series

Ammann, Manuel; Süss, Stephan

doi:10.1080/13518470902853368

Cited by 18 publications

(4 citation statements)

References 29 publications

(7 reference statements)

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“…As far as we are aware, Demarta and McNeil (2005) were the first to suggest constructing a skew t copula, although they employ a different form of skew t distribution. Recently, Sun et al (2008) used this copula to study dependence in the German equity markets, while Ammann and Süss (2009) used it to account for dependence between changes in volatility and equity returns. Estimation is via either simulated maximum likelihood or the EM algorithm, and they find that this skew t copula is preferable to the t copula.…”

Section: Discussionmentioning

confidence: 99%

Modelling dependence using skew t copulas: Bayesian inference and applications

Smith

Gan

Kohn

2010

J of Applied Econometrics

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SUMMARYWe construct a copula from the skew t distribution of Sahu et al. (2003). This copula can capture asymmetric and extreme dependence between variables, and is one of the few copulas that can do so and still be used in high dimensions effectively. However, it is difficult to estimate the copula model by maximum likelihood when the multivariate dimension is high, or when some or all of the marginal distributions are discrete-valued, or when the parameters in the marginal distributions and copula are estimated jointly. We therefore propose a Bayesian approach that overcomes all these problems. The computations are undertaken using a Markov chain Monte Carlo simulation method which exploits the conditionally Gaussian representation of the skew t distribution. We employ the approach in two contemporary econometric studies. The first is the modelling of regional spot prices in the Australian electricity market. Here, we observe complex non-Gaussian margins and nonlinear inter-regional dependence. Accurate characterization of this dependence is important for the study of market integration and risk management purposes. The second is the modelling of ordinal exposure measures for 15 major websites. Dependence between websites is important when measuring the impact of multi-site advertising campaigns. In both cases the skew t copula substantially outperforms symmetric elliptical copula alternatives, demonstrating that the skew t copula is a powerful modelling tool when coupled with Bayesian inference.

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Section: Discussionmentioning

confidence: 99%

Modelling dependence using skew t copulas: Bayesian inference and applications

Smith

Gan

Kohn

2010

J of Applied Econometrics

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“…However, due to its symmetric nature it cannot account for the asymmetry observed in the data. The skewed Student's t-copula is an alternative proposed by [43] which was found to account for asymmetric dependencies in financial data [44,45]. It captures the empirical dependence structure of the original returns better than the K-copula due to the presence of an additional parameter which accounts for the asymmetry [26].…”

Section: Comparison With the K-copulamentioning

confidence: 99%

Dependence structure of market states

Chetalova¹,

Wollschläger²,

Schäfer³

2015

J. Stat. Mech.

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Abstract. We study the dependence structure of market states by estimating empirical pairwise copulas of daily stock returns. We consider both original returns, which exhibit time-varying trends and volatilities, as well as locally normalized ones, where the non-stationarity has been removed. The empirical pairwise copula for each state is compared with a bivariate K-copula. This copula arises from a recently introduced random matrix model, in which non-stationary correlations between returns are modeled by an ensemble of random matrices. The comparison reveals overall good agreement between empirical and analytical copulas, especially for locally normalized returns. Still, there are some deviations in the tails. Furthermore, we find an asymmetry in the dependence structure of market states. The empirical pairwise copulas exhibit a stronger lower tail dependence, particularly in times of crisis.

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“…Recent research has highlighted in particular the inadequacy of this approach to take account of influences of asymmetries in individual distributions and in dependence, occurrence of extreme events and the complexity in the dependence structure of asset returns as documented in papers such as Aït‐Sahalia and Brandt (), Hong et al. () and Ammann and Suss (). These effects can fundamentally affect portfolio performance and the corresponding investment decision.…”

Section: Introductionmentioning

confidence: 99%

Optimal Currency Composition for China's Foreign Reserves: A Copula Approach

et al. 2014

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. This paper investigates the optimal currency composition for a country's foreign reserves. In the context of China, we examine the asymmetry fat-tails and complex dependence structure in distributions of currency returns. A skewed, fat-tailed, and pair-copula construction is then built to capture features of higher moments. In a D-vine copula approach, we show that under the disappointment aversion effect, the central bank in our model can achieve sizeable gains in expected economic value from switching from the mean-variance to copula modelling. We find that this approach will lead to an optimal currency composition that allows China to have more space for international currency diversification while maintaining the leading position of the US dollar in the currency shares of China's reserves._________________________________

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Asymmetric dependence patterns in financial time series

Cited by 18 publications

References 29 publications

Modelling dependence using skew t copulas: Bayesian inference and applications

Modelling dependence using skew t copulas: Bayesian inference and applications

Dependence structure of market states

Optimal Currency Composition for China's Foreign Reserves: A Copula Approach

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