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This paper investigates the structure of dependence among twelve European markets and among twelve Asian-Pacific markets. The dynamic of the dependence structure is described by a two-state regime switching model. The dependence structure during a bull phase is modelled by the Gaussian copula, while dependence during a bear phase is modelled by the...
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Citations
... Previous research, such as Pastpipatkul et al. (2015) and Aloui and Aı €ssa (2016), primarily delved into the dynamic relationships among energy, stock, and currency markets using canonical (C)-vines and drawable (D)-vines copula models. St€ ober and Czado (2014) focused on modeling nine daily exchange rates using an R-vine approach, while Gurgul and Machno (2016) explored sovereign CDS markets in G7 and BRICS, alongside crude oil, gold, stock indices, exchange rates, freight indices, and copper prices through dynamic R-vine copulas. ...
Purpose
The primary purpose of this study is to unveil the relationship between oil prices and exchange rates, with a specific focus on five major oil-importing countries. By examining this relationship, the research aims to provide valuable insights for policymakers, investors and stakeholders operating in the global economic landscape.
Design/methodology/approach
The study employs a methodological approach to ensure robust and reliable findings. First, we assess the stationarity of the time series data to establish a solid analytical foundation. Subsequently, we construct GARCH(1,1) models to capture the persistence of the volatilities inherent in the data. Building upon this, we propose the novel application of the Markov-switching R-vine copula approach, which enables us to capture structural changes and measure the dependencies between oil prices and exchange rates.
Findings
Our findings uncover significant negative relationships between oil prices and exchange rates across the examined economies while revealing varying degrees of interdependency among these variables. Notably, we elucidate distinct tail dependence structures, encompassing both symmetric and asymmetric aspects, which hold profound implications for risk assessment and portfolio management strategies. Furthermore, this study confirms the presence of regime-switching dynamics, elucidating how the co-movement patterns between oil prices and exchange rates evolve across different states or regimes, reflecting the dynamic nature of these interconnected markets.
Originality/value
The originality and value of this study lie in its comprehensive approach to understanding the relationship between oil prices and exchange rates. By accounting for structural changes and regime-switching behaviors, the research provides a nuanced understanding of the complex dynamics at play. The novel application of the Markov-switching R-vine copula approach contributes to the methodological advancement in this field of study. Furthermore, the insights derived from this research offer practical implications for policymakers, investors and stakeholders navigating the complexities of the global economic landscape, enabling them to make informed decisions and develop effective strategies to mitigate risks and capitalize on opportunities.
... 和 Machno[164] 采用机制转换 R-藤 copula 模型分别刻画了欧洲 股票市场和亚太股票市场之间的动态相依结构, 并以预期损失为风险测度进行了有效的前沿分析. 研 究发现, 欧洲市场的最优投资组合风险更大.Poignard 和 Fermanian [165] 基于藤 GARCH 模型动态生 成多元资产收益的条件相关矩阵, 并采用最小方差模型验证了该模型预测的相关矩阵的准确性. ...
... In higher dimensions r-vines are a flexible class of mulivariate distributions. This type of copulas allows for flexible modelling of asymmetric and nonlinear dependence patterns Gurgul and Machno (2016). For comparison purposes we estimated such models and it turns out that on average log-likelihoods for individual model from copulas were smaller than from HCR. ...
While we would like to predict exact values, the information available, being incomplete, is rarely sufficient - usually allowing only conditional probability distributions to be predicted. This article discusses hierarchical correlation reconstruction (HCR) methodology for such a prediction using the example of bid-ask spreads (usually unavailable), but here predicted from more accessible data like closing price, volume, high/low price and returns. Using HCR methodology, as in copula theory, we first normalized marginal distributions so that they were nearly uniform. Then we modelled joint densities as linear combinations of orthonormal polynomials, obtaining their decomposition into mixed moments. Then we modelled each moment of the predicted variable separately as a linear combination of mixed moments of known variables using least squares linear regression. By combining these predicted moments, we obtained the predicted density as a polynomial, for which we can e.g. calculate the expected value, but also the variance to determine the uncertainty of the prediction, or we can use the entire distribution for, e.g. more accurate further calculations or generating random values. 10-fold cross-validation log-likelihood tests were conducted for 22 DAX companies, leading to very accurate predictions, especially when individual models were used for each company, as significant differences were found between their behaviours. An additional advantage of using this methodology is that it is computationally inexpensive; estimating and evaluating a model with hundreds of parameters and thousands of data points by means of this methodology takes only a second on a computer.
... The Student-t d-vine copula is acknowledged for providing the best fit compared with the Gumbel d-vine, and the bivariate Student-t, Gaussian and Clayton copulas. Gurgul and Machno (2016) through the implementation of regular vine copulas of the Gaussian and mixed types (e.g., consisting of the Gaussian, Stduent-t, Gumbel, Joe-Frank, Clayotn-Gumbel) on stock markets from the Asia Pacific region (Japan, China, Taiwan, among others) and Europe (France, Germany, among others) identify stronger nonlinear dependence in the European stock markets, relative to those of the Asia Pacific region. Aloui and Ben Aïssa (2016) using vine copula models show that the time-varying codependence of energy, stock and currency markets is significantly symmetric. ...
The aim of this paper is to investigate the regional interdependence structure of energy equities in the US and in the EU. Based on weekly stock prices of 28 big energy firms in the two regions from 2008 to 2019, we compare the efficiency of using bivariate or multivariate copulas to describe the dependence structure of energy equities. Furthermore, we investigate the impact of the choice between these two methods on the performance of energy equity portfolios. Our empirical results show that multivariate copulas, such as C-Vine, allow to better describe the dependence structure of energy equities. We also find that there is a stronger and more complex dependence structure among EU energy equities than among US energy equities. Our scenario analysis also shows that the dependence structure is stronger during the GFC while being weaker during the ESDC. More importantly, the correlation matrix obtained from the multivariate copula method allows to obtain optimal mean-CVaR portfolios with a higher performance than that from the bivariate copula method. More importantly, optimal portfolios constituted with multivariate copulas allow to reduce the portfolio’s sensitivity to oil prices.
... The authors observed how the risk structure of a portfolio changes over time based on the developed model. Gurgul and Machno (2016) investigated the interdependence of financial markets among twelve European countries and among twelve Asia-Pacific countries using stock market indices. The authors utilized regime-switching copula. ...
... In this work, only a few of the most relevant are mentioned. First of all, the works related to the "contagion" effect ought to be mentioned, the empirical evidence of which is made manifest when the financial asset prices quoted in different sized markets-with dissimilar structures and different geographical locations-react simultaneously to disturbances generated either in any of them or in remote and unrelated markets (Forbes and Rigobon, 2002;Gurgul and Machno, 2016). An example is the Subprime Mortgage Crisis 2 of 2007-2012-considered the first global crisis since the Great Depression of the 1930s-, which had significant influence on the behavioral pattern of the stock yields worldwide and increased the levels of correlation between markets (e.g., Ffrench-Davis, 2001;Aloui et al., 2013;Schwert, 2011;Slimane et al., 2013;Bekaert et al., 2014). ...
... This interest is justified because such dependent relationships affect decisions of international diversification, risk management, asset valuation, and portfolio development (Boubaker and Sghaier, 2014). On an ad hoc basis, Gurgul and Machno (2016) maintain that the study on the transmission of the effects caused by extraordinary events or phenomena beyond borders is important not only for investors, but also for the governments. In the case of the latter, the transmission of effects at the international level is relevant due to how economic policy must respond to the impact of international investment decisions on the exchange rate and inflation. ...
The intensity and speed with which the effects of monetary and fiscal policies are transmitted from one financial market to another is of paramount importance to calibrate with precision the decisions of the corresponding authorities. Similarly, the transmission of the effects caused by unexpected shocks in one market and their impact on the behavior of financial assets prices in other markets requires a better understanding of the nature of the response. However, most published studies have used methodologies that assume the normality of returns and, for that reason, their results are questionable. While new methodologies that are robust to the non-normality of the returns have begun to be used, there still is much work to be done. This paper contributes to the study of the dependency among the indices of four Latin American stock market indices (IPC, IPSA, IBOVESPA and MERVAL) using copulas analysis. The main contribution of this study with respect to previous works is obtaining the level of dependency of the queues for the pairs formed by the IPC index of Mexico and each one of the other three Latin American markets indices in the sample.
... In this work, only a few of the most relevant are mentioned. First of all, the works related to the "contagion" effect ought to be mentioned, the empirical evidence of which is made manifest when the financial asset prices quoted in different sized markets-with dissimilar structures and different geographical locations-react simultaneously to disturbances generated either in any of them or in remote and unrelated markets (Forbes and Rigobon, 2002;Gurgul and Machno, 2016). An example is the Subprime Mortgage Crisis 2 of 2007-2012-considered the first global crisis since the Great Depression of the 1930s-, which had significant influence on the behavioral pattern of the stock yields worldwide and increased the levels of correlation between markets (e.g., Ffrench-Davis, 2001;Aloui et al., 2013;Schwert, 2011;Slimane et al., 2013;Bekaert et al., 2014). ...
... This interest is justified because such dependent relationships affect decisions of international diversification, risk management, asset valuation, and portfolio development (Boubaker and Sghaier, 2014). On an ad hoc basis, Gurgul and Machno (2016) maintain that the study on the transmission of the effects caused by extraordinary events or phenomena beyond borders is important not only for investors, but also for the governments. In the case of the latter, the transmission of effects at the international level is relevant due to how economic policy must respond to the impact of international investment decisions on the exchange rate and inflation. ...
La intensidad y velocidad con la cual se transmiten los efectos de la política monetaria y fiscal de un mercado financiero a otro es de primordial importancia para calibrar con precisión las decisiones de las autoridades responsables. De manera similar, los efectos provocados por shocks inesperados en un merca¬do sobre el comportamiento de los precios de los activos financieros de otros mercados requieren una me¬jor comprensión de la naturaleza de la respuesta. Sin embargo, la mayoría de los estudios publicados sobre este tema han empleado metodologías que asumen normalidad en la distribución de los rendimientos y, por esa razón, sus resultados son cuestionables. Aunque en años recientes se han comenzado a utilizar metodologías robustas a la no-normalidad, aún falta mucho trabajo por realizar. Este artículo contribuye al estudio de la dependencia entre los índices de cuatro bolsas de valores latinoamericanas (el IPC de México, el IPSA de Chile, el IBOVESPA de Brasil, y el MERVAL de Argentina) mediante la metodología de Análisis de Cópulas. La principal contribución de este estudio con respecto a trabajos anteriores es la obtención del nivel de dependencia de las colas para los pares de índices formados por el IPC de México y cada uno de los otros tres índices latinoamericanos de la muestra.
... Moreover, this is the first time we apply a Markov regime-switching vine copula model to bonds. 3 In fact, Chollete et al. (2009) studied weekly equity index returns of the G5 and Latin America via a C-vine model; Stöber and Czado (2014) used an R-vine to model 9 daily exchange rates; and finally, Gurgul and Machno (2016) exploited 12 European and 12 Asian-Pacific daily stock market indexes through an R-vine. No further researches have been conducted on regime-switching multivariate copulas except the aforementioned three papers, other studies focus on the bivariate case, i.e., applied on a pair of markets at a time, even when studying a large group of countries. ...
Multidimensional dependence in financial markets has motivated the conception of copulas as a tool to analyze nonlinear connections. However, the dynamics generating the dependence structure is still considered unchanged, whether during turmoil or stable periods, and the curse of dimensionality prevents researchers from detecting the regime shifting that may connect financial markets. In this paper, we develop a tractable Markov regime-switching C-vine and D-vine under the symmetrized Joe-Clayton copula, capable of detecting lower and upper tail dependencies separately. Application is conducted on twelve government bonds, the U.S. and eleven European bonds belonging to the Eurozone. Results show that the regime-switching copula models explain the dynamics of data dependence better than the single-regime copula, which indicates the presence of a contagion effect. Furthermore, for Eurozone bond markets, the contagion remains in its high state since the global financial crisis of 2008 and European sovereign debt crisis of 2009, with a transmission path from core to stressed countries.
