Re-examination of international bond market dependence: Evidence from a pair copula approach

The finance literature provides substantial evidence on the dependence between international bond markets across developed and emerging countries. Early works in this area were based on linear models and multivariate GARCH models. However, based on the limitations of these models this paper re-examines the non-linearity, multivariate and tail dependence structure between government bond markets of the US, UK, Japan, Germany, Canada, France, Italy, Australia and the Eurozone, from January 1970 to February 2019 using ARMA-GARCH based pair- copula models. We find that the bond markets in our sample tend to have both upper tail dependence in terms of positive shocks and lower tail dependence in terms of negative shocks. The estimated C-vine shows Eurozone has the highest average dependency. The D-vine, with optimal chain dependency structure shows the best order of connectedness to be the UK, the USA, Italy, Japan, Eurozone, France, Canada, Germany and Australia. The R-vine copula results underline the complex dynamics of bond market relations existing between the selected economies. The estimated R-vine shows Eurozone, Germany and Australia are the most inter-connected nodes. The multivariate distribution structure (interdependency) of bond markets for all countries were modelled with the C-vine, D-vine and R-vine copulas. In this application, the R-vine copula allows for detailed modelling of all bond markets and hence provides a more accurate goodness of fit and mean square error for the interdependency between all markets. In light of the changing volatility in bond markets, we conduct additional tests using time-varying copulas and find that the dependence structure among the bond markets examined is time-varying with the dynamic dependence parameter plots revealing that the nature of the dependence structure is intense during crisis periods.     

Commodity market financialization,herding and signals: An asymmetric GARCH R-vine copula approach

Institutional investors have significantly increased their exposure to commodity futures after 2004 in the process of commodity market financialization, raising questions about the risk-sharing and price-discovery functions of the market. We identify some symptoms of financialization through examining S&P500, JPM bond index, and 18 S&P GSCI excess return indices, employing ARMA-GARCH R-vine copula approach that can flexibly model high-dimensional multivariate asymmetric tail dependence. We discover three trends: an increased resemblance between the news impact curve of stocks and those of commodities; an increased bi-variate stock-commodity tail dependence; and an increased multivariate tail-dependence across all commodities. We also explore the market structural change underlying these symptoms using an augmented news impact curve. We suggest and provide evidence that herding, in addiction to leverage effect, explains the observed symptoms. The findings have profound implications for commercial hedgers and financial traders, and for regulators who are concerned about the functionalities of commodity futures market.     

The Euro and European financial market dependence

A time-varying copula model is used to investigate the impact of the introduction of the Euro on the dependence between 17 European stock markets during the period 1994–2003. The model is implemented with a GJR-GARCH-MA-t model for the marginal distributions and the Gaussian copula for the joint distribution, which allows capturing time-varying, non-linear relationships. The results show that, within the Euro area, market dependence increased after the introduction of the common currency only for large equity markets, such as in France, Germany, Italy, the Netherlands and Spain. Structural break tests indicate that the increase in financial market dependence started around the beginning of 1998 when Euro membership was determined and the relevant information was announced. The UK and Sweden, but not other European countries outside the Euro area, are found to exhibit an increase in equity market co-movement, which is consistent with the interpretation that these countries may be expected to join the Euro in the future.     

On International Consumption Risk Sharing,Financial Integration and Financial Development

This article investigates the empirical link between international consumption risk sharing, financial integration, and financial development for a group of twenty-nine developed and developing countries in the G7, the Euro area, and the OECD. Estimation results indicate that (1) risk sharing in the Euro area is higher than those in the G-7 and the OECD, and (2) a higher degree of risk sharing is associated with a greater degree of financial integration and a lower level of financial development. These results suggest that more financially integrated countries might be better able to insure themselves against idiosyncratic income shocks and countries with more developed financial markets might tend to engage in less consumption risk sharing with other countries thanks to their own sophisticated financial markets. Holding financial integration and financial development equal, countries in the Euro area engage in significantly more risk sharing than the ones in the G7 and the OECD.     

International spillovers from Euro area and US credit and demand shocks: A focus on emerging Europe

In this paper, we examine the international effects of contractions in loan supply, loan demand and aggregate demand in the euro area and the USA. All three shocks have been at the forefront in spreading stress during the period of the global financial crisis and in particular so to countries that are strongly integrated with the euro area. We find that these shocks decrease international output and total credit to a varying degree. Loan demand and aggregate demand shocks in the euro area trigger significant negative spillovers on output in most other regions. Evidence for global negative output effects of euro area loan supply shocks is fraught with considerable estimation uncertainty. When these three types of shocks emanate from the USA, we find significant negative spillovers on output also for loan supply shocks. In general, international effects on total credit are an order of magnitude larger than those on output, with again more evidence that is significant for US than euro area shocks. Last, and taking a regional stance, our results indicate that economies from emerging Europe are most vulnerable to all shocks considered. Through their strong economic integration with the euro area, these economies are likewise exposed to euro area and US shocks, and spillover effects are often larger than the domestic response in the country of shock-origin.     

Nonlinear term structure dependence: Copula functions,empirics, and risk implications

This paper documents nonlinear cross-sectional dependence in the term structure of US-Treasury yields and points out risk management implications. The analysis is based on a Kalman filter estimation of a two-factor affine model which specifies the yield curve dynamics. We then apply a broad class of copula functions for modeling dependence in factors spanning the yield curve. Our sample of monthly yields in the 1982–2001 period provides evidence of upper tail dependence in yield innovations; i.e., large positive interest rate shocks tend to occur under increased dependence. In contrast, the best-fitting copula model coincides with zero lower tail dependence. This asymmetry has substantial risk management implications. We give an example in estimating bond portfolio loss quantiles and report the biases which result from an application of the normal dependence model.     

Balance sheet effects on monetary and financial spillovers: The East Asian crisis plus 20

We study how the financial conditions in the Center Economies [the U.S., Japan, and the Euro area] impact other countries over the period 1986 through 2015. Our methodology relies upon a two-step approach. We focus on five possible linkages between the center economies (CEs) and the non-Center economics, or peripheral economies (PHs), and investigate the strength of these linkages. For each of the five linkages, we first regress a financial variable of the PHs on financial variables of the CEs while controlling for global factors. Next, we examine the determinants of sensitivity to the CEs as a function of country-specific macroeconomic conditions and policies, including the exchange rate regime, currency weights, monetary, trade and financial linkages with the CEs, the levels of institutional development, and international reserves. Extending our previous work (Aizenman et al., 2016), we devote special attention to the impact of currency weights in the implicit currency basket, balance sheet exposure, and currency composition of external debt. We find that for both policy interest rates and the real exchange rate (REER), the link with the CEs has been pervasive for developing and emerging market economies in the last two decades, although the movements of policy interest rates are found to be more sensitive to global financial shocks around the time of the emerging markets’ crises in the late 1990s and early 2000s, and since 2008. When we estimate the determinants of the extent of connectivity, we find evidence that the weights of major currencies, external debt, and currency compositions of debt are significant factors. More specifically, having a higher weight on the dollar (or the euro) makes the response of a financial variable such as the REER and exchange market pressure in the PHs more sensitive to a change in key variables in the U.S. (or the euro area) such as policy interest rates and the REER. While having more exposure to external debt would have similar impacts on the financial linkages between the CEs and the PHs, the currency composition of international debt securities does matter. Economies more reliant on dollar-denominated debt issuance tend to be more vulnerable to shocks emanating from the U.S.     

European financial market dependence: An industry analysis

This paper uses a copula model to investigate the degree and determinants of European market dependence across 10 industries in 12 Euro zone and 8 non-Euro zone stock markets during the period 1992–2011. Most of the industries in Euro countries show a dependence increase with the Euro-area after the introduction of the Euro. The effects are strongest in countries with larger market capitalization and in the Financials, Industrials, Consumer Goods, Utilities, Technology and Telecommunications industries. Overall, the export intensity, interest rate sensitivity and competitiveness of an industry and the financial development and economic openness of a country are the most important determinants of changes in equity market dependence. The period around the Lehman collapse also shows higher equity market dependence between European countries, while the lower dependence increase during the period of the recent European sovereign debt crisis suggests that country-specific factors may matter more than before.     

Financial stress transmission between the U.S. and the Euro Area

This paper examines financial stress transmission between the U.S. and the Euro Area. To better understand the linkages between financial stress in the two regions, we construct a financial stress index for the U.S. similar to the Composite Indicators of Systemic Stress (CISS) that has been developed for the Euro Area with a focus on systemic risk. Using weekly data from 2000 to 2021 and Granger predictability in distribution test, we analyze stress transmission in “normal” times as well as under unusually high and low stress episodes. While we document unilateral transmission from the U.S. to the Euro Area under normal conditions based on the center of the distribution, tail dependence tests and impulse response analysis show significant bilateral transmission, particularly in unusually high financial stress episodes. This holds true for aggregate indices as well as the subindicators of financial stress in various financial markets. As such, there must be global efforts to contain financial crises and ensure a strong and resilient financial system.     

Analysing financial contagion and asymmetric market dependence with volatility indices via copulas

This paper explores the cross-market dependence between five popular equity indices (S&P 500, NASDAQ 100, DAX 30, FTSE 100, and Nikkei 225), and their corresponding volatility indices (VIX, VXN, VDAX, VFTSE, and VXJ). In particular, we propose a dynamic mixed copula approach which is able to capture the time-varying tail dependence coefficient (TDC). The findings indicate the existence of financial contagion and significant asymmetric TDCs for major international equity markets. In some situations, although contagion cannot be clearly detected by stock index movements, it can be captured by dependence between volatility indices. The results imply that contagion is not only reflected in the first moment of index returns, but also the second moment, i.e. the volatility. Results also show that dependence between volatility indices is more easily influenced by financial shocks and reflects the instantaneous information faster than the stock market indices.     

Multivariate dependence of implied volatilities from equity options as measure of systemic risk

This paper presents a methodology to examine the multivariate tail dependence of the implied volatility of equity options as an early warning indicator of systemic risk within the financial sector. Using non-parametric methods of estimating changes in the dependence structure in response to common shocks affecting individual risk profiles, possible linkages during periods of stress are quantifiable while recognizing that large shocks are transmitted across financial markets differently than small shocks. Before and during the initial phase of the financial crisis, we find that systemic risk increased globally as early as February 2007 — months before the unraveling of the U.S. subprime mortgage crisis and long before the collapse of Lehman Brothers. The average (multivariate) dependence among a global sample of banks and insurance companies increased by almost 30% while joint tail risk declined by about the same order of magnitude, indicating that co-movements of large changes in equity volatility were more likely to occur and responses to extreme shocks became more differentiated as distress escalated. The key policy consideration flowing from our analysis is that complementary measures of joint tail risk at high data frequency are essential to the robust measurement of systemic risk, which could enhance market-based early warning mechanisms as part of macroprudential surveillance.     

International transmission and business-cycle effects of financial stress

We analyze the international transmission of financial stress and its effects on global economic activity. Our analysis is based on country-specific monthly financial stress indices (FSIs) over the sample period 1970–2012 for 20 major economies. First, we show that co-movement between the FSIs increases during major financial crises and towards the end of our sample period. Second, we show that the risk of large financial stress spillovers to an economy increases with its level of economic openness. Third, we show – using a global VAR (GVAR) model – that (i) a financial stress shock in the US quickly transmits internationally, (ii) financial stress shocks have lagged but persistent negative effects on economic activity, and (iii) that a negative US demand shock induces only limited financial stress on a global scale. Finally, we show that spillovers of financial stress run mainly from advanced to emerging economies and not in the opposite direction.     

International transmission of financial shocks in an estimated DSGE model

This paper investigates the transmission of financial shocks across large economies. To quantify these effects, we estimate a two-region open economy DSGE model that includes frictions in credit markets. The baseline model fails to replicate the high correlation between the U.S. and Euro Area macroeconomic variables. Allowing for an ad hoc, cross-regional correlation in financial shocks considerably improves the model's ability to match the data. We extend the baseline model by including global banks, and generate an endogenous cross-regional correlation of borrowing costs. Simulations demonstrate large spillover effects, and highlight the importance of including frictions in international financial contracts for more accurately capturing the high cross-regional correlation.     

Spillover effects from Euro area monetary policy across Europe: A factor-augmented VAR approach

I analyze spillover effects from a Euro area monetary policy shock to fourteen European countries outside the Euro area. The analysis is based on a factor-augmented VAR model with two blocks, which exploits a large cross-country data set. After a Euro area monetary policy expansion, production increases in most non-Euro area countries, whereas short-term interest rates and financial uncertainty decline. These effects are on average comparable to the responses in the aggregate Euro area. However, the size of spillover effects varies with country characteristics. Spillovers on production are larger in non-Euro area economies with higher trade openness, whereas financial variables react to a higher extent in countries with higher financial integration. Regarding the exchange rate regime, countries with fixed exchange rates show stronger spillovers both in terms of production and interest rates. Finally, prices increase in Western European economies outside the Euro area, but decline or do not respond in Central and Eastern Europe.     

The transmission of market shocks and bilateral linkages: Evidence from emerging economies

The linkage between emerging and developed economies spans beyond the usual trade in goods and services. Underlying trade is the flow of capital for foreign direct investment and for speculation in markets, which renders emerging economies vulnerable to shocks from the developed world. As such, equity return volatility in emerging markets is partly attributable to this dependence. To gauge the importance of bilateral economic and cultural factors in driving economic integration, we adopt a two-step process. First, we use Diebold and Yilmaz's spillover index methodology to extract spillover indices representative of the return volatility spillover effects of the United States, the developed portion of the Euro area, and Japan on financial markets in Asia, the Gulf Cooperation Council countries, Eastern and Central Europe, Africa, and Latin America. Second, we test whether these indices are governed by economic and cultural factors. Our results show that the spillover effects vary across markets and that a strong correlation exists with the volume of trade, security investment, common language, distance, and market capitalization.     

Diversification evidence from international equity markets using extreme values and stochastic copulas

Tail dependence plays an important role in financial risk management and determination of whether two markets crash or boom together. However, the linear correlation is unable to capture the dependence structure among financial data. Moreover, given the reality of fat-tail or skewed distribution of financial data, normality assumption for risk measure may be misleading in portfolio development. This paper proposes the use of conditional extreme value theory and time-varying copula to capture the tail dependence between the Australian financial market and other selected international stock markets. Conditional extreme value theory enables the model adequacy and the tail behavior of individual financial variable, while the time-varying copula can fully disclose the changes of dependence structure over time. The combination of both proved to be useful in determining the tail dependence. The empirical results show an outperformance of the model in the analysis of tail dependence, which has an important implication in cross-market diversification and asset pricing allocation.     

Stock–bond dependence and flight to/from quality

This paper investigates the stock–bond dependence structure using a dependence-switching copula model. The model allows stock–bond dependence to switch between positive dependence regimes (contagions or crashes of the two markets during downturns or booms in both markets during upturns) and negative dependence regimes (flight-to-quality from stock markets to bond markets or flight-from-quality from bond markets to stock markets). Using data from four developed markets including the US, Canada, Germany, and France for the period between January 1985 and August 2022, we find that the within-country stock–bond (extreme) dependence could be both positive and negative. In the positive dependence regimes, the stock–bond dependence is asymmetric with stronger left tail dependence than the right tail dependence, giving evidence of a higher likelihood of joint stock–bond market crashes or contagions during market downturns than the collective stock–bond market booms. Under the negative dependence regimes, we find both flight-from-quality and flight-to-quality, with flight-to-quality being more dominant in the North American markets while flight-from-quality is more prominent in the European markets. Further, the dependence switches between positive and negative regimes over time. Moreover, the dependence is mainly in the positive regimes before 2000 while mostly in the negative regimes after that, indicating contagions mostly before 2000 and flights afterwards. Further, the dependence switches between positive and negative regimes around financial crises and the COVID-19 pandemic. These results greatly enrich the findings in the existing literature on the co-movements of stock–bond markets and are important for risk management and asset pricing.     

Assessing High-Risk Scenarios by Full-Range Tail Dependence Copulas

Copulas with a full-range tail dependence property can cover the widest range of positive dependence in the tail, so that a regression model can be built accounting for dynamic tail dependence patterns between variables. We propose a model that incorporates both regression on each marginal of bivariate response variables and regression on the dependence parameter for the response variables. An ACIG copula that possesses the full-range tail dependence property is implemented in the regression analysis. Comparisons between regression analysis based on ACIG and Gumbel copulas are conducted, showing that the ACIG copula is generally better than the Gumbel copula when there is intermediate upper tail dependence. A simulation study is conducted to illustrate that dynamic tail dependence structures between loss and ALAE can be captured by using the one-parameter ACIG copula. Finally, we apply the ACIG and Gumbel regression models for a dataset from the U.S. Medical Expenditure Panel Survey. The empirical analysis suggests that the regression model with the ACIG copula improves the assessment of high-risk scenarios, especially for aggregated dependent risks.     

Testing the Gaussian copula hypothesis for financial assets dependences

Abstract

Using one of the key properties of copulas that they remain invariant under an arbitrary monotonic change of variable, we investigate the null hypothesis that the dependence between financial assets can be modelled by the Gaussian copula. We find that most pairs of currencies and pairs of major stocks are compatible with the Gaussian copula hypothesis, while this hypothesis can be rejected for the dependence between pairs of commodities (metals). Notwithstanding the apparent qualification of the Gaussian copula hypothesis for most of the currencies and the stocks, a non-Gaussian copula, such as the Student copula, cannot be rejected if it has sufficiently many ‘degrees of freedom’. As a consequence, it may be very dangerous to embrace blindly the Gaussian copula hypothesis, especially when the coefficient of correlation between the pairs of assets is too high, such that the tail dependence neglected by the Gaussian copula can became large, leading to the ignoring of extreme events which may occur in unison.     

Combining random forest and copula functions: A heuristic approach for selecting assets from a financial crisis perspective

In this paper we propose a heuristic strategy aimed at selecting and analysing a set of financial assets, focusing attention on their multivariate tail dependence structure. The selection, obtained through an algorithmic procedure based on data mining tools, assumes the existence of a reference asset we are specifically interested to. The procedure allows one to opt for two alternatives: to prefer those assets exhibiting either a minimum lower tail dependence or a maximum upper tail dependence. The former could be a recommendable opportunity in a financial crisis period. For the selected assets, the tail dependence coefficients are estimated by means of a proper multivariate copula function. Copyright © 2010 John Wiley & Sons, Ltd.