Editorial Introduction to the Special Issue ...

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Sep 18, 2013 - financial systems of the US, Europe (with a special focus on .... Freddie Mac, Lehman Brothers and American International Group and.
International Review of Financial Analysis 33 (2014) iii–iv

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International Review of Financial Analysis

Editorial Introduction

Special Issue: Comovement and Contagion in Financial Markets

The analysis of contagion has a long history in economics and, particularly, in finance.1 The relevance of this central issue springs from the wide agreement that financial markets are continuously invaded by information flows. The latter are reinforced by the growing integration between capital markets, and increase significantly during market turmoil, leading in some cases to global systemic events, as it was the case of the recent 2007–2009 financial crisis. This crisis has been crucially characterized by its virulence and brutality. The shock wave initiated by the collapse of Lehman Brothers on September 15, 2008 was indeed instantly spread out to the international financial markets. The increasing comovements and interconnections between financial systems determined substantially the intensity of spreading. The subsequent instability in both financial and real spheres, along with the magnitude of social costs in most of the “affected” countries, raised the need for a better understanding of diffusion dynamics. To give a brief overview of the issue, the relevant literature on financial contagion attempts to analyze the propagation mechanisms fuelling financial crises. The most commonly explored channels enclose real or trade linkages (Gerlach & Smets, 1995), financial linkages via portfolio rebalancing (Kodres & Pritsker, 2002), and liquidity shocks (Allen & Gale, 2000). Nevertheless, whether real or financial channel operates the most, remains an appealing and open question. Turning to the empirical side, research on contagion generally reports close links between financial markets during times of crisis (Calvo & Reinhart, 1996; Forbes & Rigobon, 2002; King & Wadhwani, 1990; Lee & Kim, 1993). More specifically, to achieve reliable evidence of contagion, studies seek to detect changes in interconnections among different markets over calm and turbulent periods. If those links remain stable over time, shocks tend to be transmitted through fundamentals. On the contrary, reinforcement of these interrelationships during crisis episodes favors the contagion scenario. From a methodological point of view, a lot of statistical and econometric methods have been utilized in the effort to understand and measure spillover effects. Beyond the traditional correlation-based test implemented by King et al. (1994) and its corrected version introduced by Forbes and Rigobon (2002), the literature suggests a battery of noteworthy methodologies, including the co-exceedance test of Bae et al. (2003), the conditional co-skewness and co-kurtosis tests of Fry et al. (2010), the copula-based approach of Busetti and Harvey (2011) as well as the mutual jumps test of Aït-Sahalia et al. (forthcoming), among others. In this line, the present special issue aims to contribute to the current debate regarding the nature of contagion and its amplification channels by presenting up-to-date tools and in-depth empirical applications in a

1

See for e.g., Forbes and Rigobon (2001).

http://dx.doi.org/10.1016/S1057-5219(14)00075-1

variety of data sets. It consists of nine articles listed and discussed beneath. Podlich and Wedow attempt to investigate factors being at the source of the comovement of financial institutions’ credit spreads. Their research is built on two main directions. In a first stage, the analysis determines the strength and direction of contagious effects invading the financial systems of the US, Europe (with a special focus on Germany), Asia, and different emerging countries. Then, they give emphasis to the impact of cross-border contagion into dealer and non-dealer banks highlighting the role of the over-the-counter (OTC) markets as shocks amplifiers. With means of uni- and multivariate GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models, they provide evidence in favor of a strong influence of the US and European financial systems to the German financial market which in turn seems to be seriously affected by the action of the OTC dealer banks. Dimpfl, via an alternative methodological approach, stands critically towards the concept of cointegration which is frequently used to capture eventual interrelationships between financial markets. He shows that when time series share a common stochastic trend, cointegration analysis may fail to address satisfactorily the presence of comovement. In a sample of 28 stock market indexes, the empirical findings are far to be conclusive while the detection of cointegration appears to be rather coincidental. Dufrenot and Keddad examine whether the subprime crisis exerted a significant and persistent pressure on the volatility of the Indian equity markets. In the aim at capturing long-term persistence in variance due to variables relating to the financial crisis, they suggest an autoregressive stochastic volatility model with exogenous inputs. Through an extensive empirical application they find that during the global financial distress period, the null hypothesis of uncoupling between the US and the Indian markets does not hold. Rapid spread of information from the US to the domestic markets rendered the latter illiquid by activating momentum behavior and increasing risk. Combining Extreme Value Theory (EVT) with GARCH-type models, Berger and Missong adopt an EVT-GARCH-copula framework in the effort to obtain robust value-at-risk (VaR) estimation and prediction by taking advantage of its nonlinear properties. Indeed, the empirical results reveal that the EVT-GARCH-copula model outperforms the linear versions and leads to adequate VaR estimates for a variety of asset classes, such as German stocks, national indexes and FX-rates, over both tranquil and volatile market regimes. The relevant conclusion of the paper is that the sensitivity of the VaR accuracy, observed throughout turbulent phases, can act as an early indicator of an upcoming crisis. In a way to approach the issue of extreme downside risk spillovers from a different angle, Liu performs VaR forecasts via a Markov Switching ARCH model permitting the variance to change across states. The data set consists of the US, Japan and Asia-Pacific stock markets.

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Editorial Introduction

The paper finds significant evidence for the existence of system risk running from the dominant US and Japan to the smaller markets. The dependence of empirical findings on the size and location of signal transmitter (i.e. US or Japan) along with the different market conditions (i.e. calm or crisis periods) presents evidently noticeable implications for portfolio diversification and hedging of extreme negative shocks. In the effort to apprehend the mechanism via which international equity returns respond to global shocks (i.e. monetary and oil disturbances), Jinjarak implements a multifaceted methodological approach including international asset pricing modeling, variance decomposition and cross-country estimation. The obtained results support the view that equity returns reply negatively to global shocks. Furthermore, he finds evidence that the nature of integration determines crucially the responsiveness of the equity returns to either oil shocks or Fed Funds rates across countries. Bekiros follows a quite different line of study by employing both linear and nonlinear Granger causality tests jointly with various GARCHtype processes, namely BEKK-GARCH, Constant Conditional Correlation-GARCH and Dynamic Conditional Correlation-GARCH, to explore spillover effects between the US, EU and BRIC markets. It was shown that markets became more integrated in the aftermath of the US financial crisis and the EU debt sovereign crisis. More specifically, it turns out that the detected causal linkages are nonlinear in nature implying standing policy implications both in terms of regulation and investors’ trading. Based on the concept of Granger causality, Lee and Yang attempt to analyze further the dynamic interrelationship between the US, UK and Japan stock markets. Instead of using a causality testing procedure in mean or variance, they introduce two new statistics relying upon information entropy combined with copulas to measure the strength of Granger causality in distribution. The causal linkage that has been found to be significant goes from the UK to the US while in the opposite direction it appears that spillover effects from the US to Japan stock markets slightly dominate the US-UK channel. Finally, Gao and Hu put emphasis on the informational content that entropy-based approaches may have and shed light on the quest of whether dynamic tools can send alarming signals prior to economic downturns. They examine the exposure networks of FannieMae/ Freddie Mac, Lehman Brothers and American International Group and then model their losses by a two-parameter Omori-law-like distribution for earthquake aftershocks. Their main findings suggest that entropies associated with the negative income cluster are much higher than that

of the positive income cluster. This characteristic behavior of entropy occurs before the NBER announcements of recessions. References Aït-Sahalia, Y., Cacho-Diaz, J., & Laeven, R. J. A. (2014g). Modeling financial contagion using mutually exciting jump processes”. Review of Financial Studies (forthcoming). Allen, F., & Gale, D. (2000). Financial Contagion”. Journal of Political Economy, 108, 1–33. Bae, K. H., Karolyi, G. A., & Stulz, R. M. (2003). A New Approach to Measuring Financial contagion”. Review of Financial Studies, 16, 717–763. Busetti, F., & Harvey, A. C. (2011). When is a Copula Constant? A Test for changing Relationships”. Journal of Financial Econometrics, 9, 106–131. Calvo, S., & Reinhart, C. (1996). Capital Flows to Latin America: Is There Evidence of Contagion Effects? The World Bank. Policy Research Working Paper Series, 1619, . Forbes, K. J., & Rigobon, R. (2001). Measuring Contagion: Conceptual and Empirical Issues”. In S. Claessens, & K. J. Forbes (Eds.), International Financial Contagion. : Kluwer Academic Publishers. Forbes, K. J., & Rigobon, R. (2002). No Contagion, Only Interdependence: Measuring Stock Market Co-movements?”. Journal of Finance, 57, 2223–2261. Fry, R., Martin, V. L., & Tang, C. (2010). A New Class of Tests of Contagion with Applications”. Journal of Business and Economic Statistics, 28, 423–437. Gerlach, S., & Smets, F. (1995). Contagious Speculative Attacks”. European Journal of Political Economy, 11, 5–63. King, M., Sentana, E., & Wadhwani, S. (1994). Volatility and Links Between National Stock Markets”. Econometrica, 62, 901–933. King, M., & Wadhwani, S. (1990). Transmission of Volatility between Stock Markets”. Review of Financial Studies, 3, 5–33. Kodres, L. E., & Pritsker, M. (2002). A Rational Expectations Model of Financial Contagion”. Journal of Finance, 57, 768–799. Lee, S. B., & Kim, K. J. (1993). Does the October 1987 Crash Strengthen the Co-Movements among National Stock Markets?”. Review of Financial Economics, 3, 89–102.

Catherine Kyrtsou University of Macedonia (Greece), BETA, University of Strasbourg, and EconomiX-CNRS, University of Paris Ouest, France E-mail address: [email protected]. Valérie Mignon EconomiX-CNRS, University of Paris Ouest, and CEPII, Paris, France E-mail address: [email protected]. Sessi Tokpavi EconomiX-CNRS, University of Paris Ouest, France E-mail address: [email protected]. 18 September 2013