Portfolio Diversification Strategy Via Tail‐Dependence Clustering and ARMA‐GARCH Vine Copula Approach

This study proposes a diversified portfolio construction method based on the tail dependence between the financial assets and adopting both market prior information and the exports’ subject views. In this paper, tail‐dependence clustering was applied to divide candidate assets into different groups according to their tail dependence during the crisis period and the ARMA‐GARCH vine copula‐opinion pooling approach was applied to select the minimum Conditional Value‐at‐Risk portfolio according to the clustering results. The daily closed prices of the components of DAX 20 from 3 January 2006 to 20 December 2014 were studied to illustrate the methodology. The results reveal that more than 90% of 450 possible portfolios are modelled by D‐vine structure and Student's t‐copula dominates almost all the cases for pair copula selection. As Student's t‐copula captures the symmetric tail dependence, the 450 possible portfolios do not show stronger lower tail dependence than upper tail dependence. This study contributes by combining cluster analysis with portfolios selection. It uses vine copula to capture the dependence structure among assets. Finally, it offers a flexible method to describe market and offers a strategy to construct diversified portfolios by adding the investors’ information into portfolio selection procedure at the 1‐day forecast horizon.     

The time-varying and asymmetric dependence between crude oil spot and futures markets: Evidence from the Mixture copula-based ARJI–GARCH model

This paper designs a Mixture copula-based ARJI–GARCH model to simultaneously investigate the dynamic process of crude oil spot and futures returns and the time-varying and asymmetric dependence between spot and futures returns. The individual behavior of each market is modeled by the ARJI–GARCH process. The time-varying and asymmetric dependence is captured by the Mixture copula which is composed of the Gumbel copula and Clayton copula. Empirical results show three important findings. First, jumping behavior is an important process for each market. Second, spot and futures returns do not have the same jump process. Third, the tail dependence between spot and futures markets is time-varying and asymmetric with the magnitude of upper tail dependence being slightly weaker than that of lower tail dependence.     

Commodity currencies and commodity prices: modelling static and time-varying dependence

This article employs the copula approach to study the relationship between exchange rates and commodity prices for large commodity exporters. Using data for the nominal exchange rates of four commodity currencies (Australian, Canadian and New Zealand dollars, and Norwegian krone) against the US dollar and the relevant country-specific commodity price indices, constructed on a daily basis, we find (1) a positive dependence between the values of commodity currencies and commodity indices, i.e. a commodity index increases when a respective currency appreciates and provides several explanations for this finding; (2) no major asymmetries in the tail dependence for most pairs of exchange rates and commodity indices and (3) a pronounced increase in the time-varying tail dependence following the global financial crisis.     

Diamonds and precious metals for reduction of portfolio tail risk

ABSTRACT

We study the performance of diamonds compared to gold and other precious metals in mitigating the tail risk of a diversified equity market portfolio over the period June 2007 to October 2018. Our results display a diversification benefit of some diamond indices, which also improve the portfolio reward-to-risk ratio. To corroborate this evidence, we study the dependence structure and tail dependence of diamonds and a broad equity market portfolio and compare it to the dependence obtained with gold and other precious metals. Results from fitting a bivariate copula show that the average left tail dependence reaches its minimum when diamonds are used. We also show that using shares of diamond-mining companies does not provide the same benefits.     

Asymmetric downside and upside co-movements between stock and REIT markets

This article aims to investigate whether stock and real estate investment trust (REIT) returns have asymmetric downside and upside co-movements. The investigation is carried out by employing a mixture copula with Markov-switching coefficients for weight, upper tail dependence and lower tail dependence. Empirical result demonstrates that an asymptotic independence and a positive relationship, which has greater dependence in the left tail than in the right tail, coexist. The empirical result provides useful information for making portfolio decisions. In the independent state, the inclusion of stock and REIT indices in a portfolio builds a diversified portfolio. However, a portfolio with stock and REIT assets cannot get the benefit of risk reduction in the positive dependence state.     

The dependence structure between the Canadian stock market and the USD/CAD exchange rate: a copula approach

Abstract This paper investigates the dependence structure between the real Canadian stock returns and the real USD/CAD exchange rate returns, using the Symmetrized Joe‐Clayton (SJC) copula function. We estimate the SJC copula with monthly data over the period 1995:1 to 2006:12. Our results show significant asymmetric static and dynamic tail dependence between the real stock returns and the real exchange rate returns, such that the two returns are more dependent in the left than in the right tail of their joint distribution. We explain this asymmetric dependence in terms of an asymmetric interest rate policy by Canadian monetary authorities in response to changes in the real exchange rate during sub‐periods of falling and rising commodity prices.     

Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries

This paper considers the application of copula models to study the shifts in extremal economic dependence of the Eastern European countries, i.e., Ukraine and its neighbouring countries, from 1969 to 2014. Extremal economic dependence is analysed in terms of poverty and affluence and with regard to growth rate. This paper contributes to the previous literature by applying the copula approaches to derive the measurements of the economic interdependence in terms of poverty and affluence. The received results depict the pattern of the (inter)dependence and its evolution across the analysed countries. Dependence on other countries in the extreme values can potentially be useful in adjustments of the economic policy of a country to minimize poverty and prevent high inequality.

     

Dynamic linkages between stock markets: the effects of crises and globalization

This paper investigates changes in the dynamics of linkages between selected national stock markets during the period 1995–2009. The analysis focuses on the possible effects of globalization and differences between crisis and non-crisis periods. We model the dynamics of dependencies between the series of daily returns on selected stock indices over different time periods, and compare strength of the linkages. Our tools are dynamic copula models and a formal sequential testing procedure based on the model confidence set methodology. We consider two types of dependencies: regular dependence measured by means of the conditional Spearman’s rho, and dependencies in extremes quantified by the conditional tail dependence coefficients. The main result consists of a collection of rankings created for the considered subperiods, which show how the mean level of strength of the dependencies have been changing in time. The rankings obtained for Spearman’s rho and tail dependencies differ, which allows us to distinguish between the results of crises and the effect of globalization.     

LATIN AMERICAN EXCHANGE RATE DEPENDENCIES: A REGULAR VINE COPULA APPROACH

This study implements a regular vine copula methodology to evaluate the level of contagion among the exchange rates of six Latin American countries (Argentina, Brazil, Chile, Colombia, Mexico, and Peru) from June 2005 to April 2012. We measure contagion in terms of tail dependence coefficients, following Fratzscher's (1999) definition of contagion as interdependence. Our results indicate that these countries are divided into two blocks. The first block consists of Brazil, Colombia, Chile, and Mexico, whose exchange rates exhibit the largest dependence coefficients, and the second block consists of Argentina and Peru, whose exchange rate dependence coefficients with other Latin American countries are low. We also found that most of the Latin American exchange rate pairs exhibit asymmetric behaviors characterized by nonsignificant upper tail dependence and significant lower tail dependence. These results imply that there exists contagion in Latin American exchange rates in periods of large appreciations, whereas there is no evidence of contagion during periods of currency depreciation. This empirical regularity may reflect the “fear of appreciation” in emerging economies identified by Levy‐Yeyati, Sturzenegger, and Gluzmann (2013). (JEL C32, C51, E42)     

HETEROGENEITY OR TRUE STATE DEPENDENCE IN POVERTY: THE TALE TOLD BY TWINS

The purpose of this study is to distinguish between two different reasons that poverty could persist on an individual level. This study takes advantage of the similarity within pairs of identical twins to separate family‐specific heterogeneity from true state dependence, where the experience of poverty leads to a higher risk of future poverty. The results, based on a four‐variate probit model, show the importance of true state dependence in poverty. When using a poverty measure based on disposable income, family‐specific heterogeneity explains between 21 and 25 percent of poverty persistence in the Swedish sample of twins.     

Sovereign bond market dependencies and crisis transmission around the eurozone debt crisis: a dynamic copula approach

We examine the dependency between the European government bond markets around the recent sovereign debt crisis. A dynamic copula approach is used to model the time-varying dependence structure of those government bond markets, evaluate the nature and strength of their dependencies over time, and gauge the transmission of the crisis shocks. Our results can be summarized as follows: i) the eurozone sovereign bond markets under consideration have a significant and positive dependence with the Greek and the EMU benchmark sovereign bond markets; ii) the dynamic-BB7 copula function best describes the dependence structure between these sovereign bond markets and provides evidence of asymmetric tail dependence; iii) the conditional probability of crisis transmission from Greece to other eurozone countries is higher than the other way around; and iv) Greece is the most vulnerable country when the eurozone entered into the sovereign debt crisis.     

“金砖四国”股票市场间相依结构分析

金融市场间的相依关系及其结构分析是金融风险测度、资产组合管理等金融理论和实务中的一个重要问题,而基于线性相关系数是难以正确刻画非线性条件下金融资产间的相关结构,特别是尾相依关系。为研究"金砖四国"新兴股票市场间的相依结构,文章构建了一个混合Copula模型,对"金砖四国"股票市场间的相依结构进行建模分析,并将结果与单一阿基米德Copula模型进行了比较,表明混合Copula模型既能保留单一Copula模型的特性,更能灵活、全面地刻画变量间的相依关系。实证研究的结果表明:在样本数据期间,"金砖四国"股票市场间存在非对称相关关系,相依结构上存在差异;中国上证综指波动较为剧烈,与其它三国指数间以下尾相依为主;巴西、印度、俄罗斯三国股指间的相依结构相似,联动相关性相近,并无显著的下尾相依关系。     

Tail dependence risk exposure and diversification potential of Islamic and conventional banks

This paper undertakes a rolling window comparative analysis of risks for portfolios consisting of GCC Islamic and conventional bank indices. We draw our empirical results by employing canonical, drawable and regular vine copula models, as well as by implementing a portfolio optimization method with a conditional Value-at-Risk constraint. We find evidence of higher riskiness in the group of Islamic banks relative to the group of conventional banks across each of the financial rolling window scenarios under consideration. Specifically, a greater negative (nonlinear) tail asymmetric dependence is observed in the pairs of Islamic banks’ relationships. The results also show that the optimal portfolio model supports a clear preference towards the group of conventional banks in regard to risk minimization and diversification benefits.     

A new test procedure for the choice of dependence structure in risk measurement: application to the US and UK stock market indices

The choice of an appropriate dependence structure in modelling multivariate risks is an important issue because different tail structure embedded in copula leads to a different capital requirement for the institution. We present how to select a well-specified dependence structure to given application data. Using a simple simulation technique, we develop a statistical test to assess the adequacy of a specific dependence structure. We examine the sensitivity of risk estimates to the choice of copulas using the S&P 500 and FTSE 100 stock indices.     

Relationship between oil price and exchange rate by FDA and copula

This article investigates the relationship between daily crude oil prices and exchange rates. Functional data analysis is used to show the clustering pattern of exchange rates and oil prices over the time period through high dimensional visualizations. We select exchange rates for important currencies related to crude oil prices by using the objective Bayesian variable selection method. The selected sample data exhibits non-normal distribution with fat tails and skewness. Under the non-normality of the return series, we use copula functions that do not require to assume the bivariate normality to consider marginal distribution. In particular, our study applies the popular and powerful statistical methods such as Gaussian copula partial correlations and Gaussian copula marginal regression. We find evidence of significant dependence for all considered pairs, except for the Mexican peso-Brent. Our empirical results also show that the rise in the West Texas Intermediate (WTI) oil price returns is associated with a depreciation of the US dollar.     

Dependence structure between nominal and index-linked bond returns: a bivariate copula and DCC-GARCH approach

This article investigates the dependence structure related to four French nominal and index-linked bonds with various maturities and reference indices. To achieve this aim, we estimate various copulas to select the appropriate one for our data. We also compare results obtained using the copula method with multivariate dynamic conditional correlation GARCH (DCC-GARCH) modelling. The major issue in this study is that the best copulas used to model the dependence among bond returns are the Plackett and Student models. We also find a dynamic correlation between bond returns. In particular, the relationship between nominal and indexed bonds is characterized by an asymmetric dependence. Moreover, the results obtained by the copula approach are confirmed by those obtained by multivariate GARCH modelling. Our empirical study provides a useful method that may be employed by decision-makers to quantitatively introduce dependence and spillover effects in their bond issuance policy. For investors, we propose optimal investment combinations in bonds with respect to their investment horizons.     

Portfolio management with tail dependence

Many publications, that treated with Portfolio Management, were devastating for all asset allocation models in the context of portfolios. The elimination of extreme events (asymmetric or tail dependence) during the portfolio construction process can reduce the skills of asset managers to reduce risk through diversification. The copula theory allows us to calculate an alternative to measure the dependence of extreme events in assets through the index lower tail dependence. We check that the strategies with tail dependence overcame Talmud rule, the Markowitz model and the model of Tu and Zhou by simulating 1,000 portfolios with 3, 5, 10 and 20 randomly selected assets from DJIA for the period 03/1990 until 12/2016. We conclude that models of tail dependence and Markowitz had more performance ex-ante than Talmud and the Tu and Zhou model for portfolios with 3, 5, 10 and 20 assets. Tail dependence models overcome Markowitz, in terms of cumulative return, in over 60% of months considered in the analysis. The results indicate that the Talmud rule should be discarded in a context of constructing portfolios with individual stocks ahead strategies with tail dependence.     

A measurement of affluence and poverty interdependence across countries: Evidence from the application of tail copula

This paper examines affluence and poverty interdependence across 185 countries and its evolution over 1969–2014. To estimate affluence and poverty interdependence and derive tail interdependences the tail copulae are applied to multivariate density function. The tail coefficients are estimated in the non-parametric way as in Schmidt and Stadtmüller (2006). The estimates show, that poverty is less interdependent and continue to decrease, while affluence has asymptotically high global dependence, meaning a higher global dependence on and sensitivity to the well-being of the affluent countries. The received results derive the pattern of the extreme interdependence and can help to identify poverty and affluence spill-over across countries and regions and calculate the average sensitivity of a country to these phenomena on the global level and can potentially help in poverty reduction strategies within the Sustainable Development Goal by the United Nations.     

Bivariate income distributions for assessing inequality and poverty under dependent samples

As indicators of social welfare, the incidence of inequality and poverty is of ongoing concern to policy makers and researchers alike. Of particular interest are the changes in inequality and poverty over time, which are typically assessed through the estimation of income distributions. From this, income inequality and poverty measures, along with their differences and standard errors, can be derived and compared. With panel data becoming more frequently used to make such comparisons, traditional methods which treat income distributions from different years independently and estimate them on a univariate basis, fail to capture the dependence inherent in a sample taken from a panel study. Consequently, parameter estimates are likely to be less efficient, and the standard errors for between-year differences in various inequality and poverty measures will be incorrect. This paper addresses the issue of sample dependence by suggesting a number of bivariate distributions, with Singh–Maddala or Dagum marginals, for a partially dependent sample of household income for two years. Specifically, the distributions considered are the bivariate Singh–Maddala distribution, proposed by Takahasi (1965), and bivariate distributions belonging to the copula class of multivariate distributions, which are an increasingly popular approach to modelling joint distributions. Each bivariate income distribution is estimated via full information maximum likelihood using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey for 2001 and 2005. Parameter estimates for each bivariate income distribution are used to obtain values for mean income and modal income, the Gini inequality coefficient and the headcount ratio poverty measure, along with their differences, enabling the assessment of changes in such measures over time. In addition, the standard errors of each summary measure and their differences, which are of particular interest in this analysis, are calculated using the delta method.     

基于消费者物价指数的养老金担保成本评估模型

探讨了以消费者物价指数为最低担保的缴费确定型养老金计划,并在应用Copula函数度量投资组合回报率与消费者物价指数增长率的相关关系基础上,建立了评估这种担保成本的模型,最后给出了担保成本的随机模拟算法。