Periods Of Financial Turmoil Research Articles

Financial Crises and Contagion: Evidence for BRIC Stock Markets

This paper proposes a new multivariate copula regime-switching model to capture non-linear relationships in four emerging stock markets, namely Brazil, Russia, India, China (BRIC) and two developed markets (U.S. and U.K.), during five recent financial crises (the Asian crisis, the Russian crisis, the tech bust and the two episodes in Brazil). We also investigate the presence of asymmetric responses in conditional variances and correlations during these periods of negative shocks, applying the asymmetric generalized dynamic conditional correlation (AG-DCC) approach. These methods go beyond a simple analysis of correlation breakdowns, analyze the second moment dynamics of stock market returns, and enable us to overcome problems arising in the existing empirical research of financial contagion. Results provide evidence that there is an asymmetric increase in dependence among stock markets during all five crises. The jump in correlations and volatilities between stable and crisis periods supports financial contagion when crises are spread to other markets. Moreover, the differences in the magnitudes of the dependence changes show that the industry-specific tech bust appears to have a larger impact than country-specific crises. Furthermore, increases in tail dependence imply that the probability of markets crashing together is higher during periods of financial turmoil. Our findings imply that policy responses to a crisis are unlikely to prevent the spread among countries, making fewer domestic risks internationally diversifiable when it is most desirable. A further finding of this study is that the multivariate regime-switching copula model captures higher level of dependence than the AG-DCC approach, possibly due to econometric reasons.

Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns

This paper proposes a new generalized autoregressive conditionally heteroskedastic (GARCH) process, the asymmetric generalized dynamic conditional correlation (AG-DCC) model. The AG-DCC process extends previous specifications along two dimensions: it allows for series-specific news impact and smoothing parameters and permits conditional asymmetries in correlation dynamics. The AG-DCC specification is well suited to examine correlation dynamics among different asset classes and investigate the presence of asymmetric responses in conditional variances and correlations to negative returns. We employ the AG-DCC model to analyze the behavior of international equities and government bonds. While equity returns show strong evidence of asymmetries in conditional volatility, little is found for bond returns. However, both equities and bonds exhibit asymmetries in conditional correlations, with equities responding stronger than bonds to joint bad news. The article also finds that, during periods of financial turmoil, equity market volatilities show important linkages, and conditional equity correlations among regional groups increase dramatically. Furthermore, in January 1999 with the introduction of the euro, we document significant evidence of a structural break in correlation although not in

Introduction: Context, Issues, and Contributions

from the Asian financial crisis, the Russian default, and the Brazilian devaluation, Argentina's President Menem recommended that his country officially replace the peso with the U.S. dollar. Motivating this proposal was a desire to strengthen the credibility of Argentine monetary arrangements. Although Argentina had maintained a currency board since 1991, interest rate differentials between peso-denominated and dollar-denominated debt widened during periods of financial turmoil, indicating that the market perceived a significant probability of devaluation. Menem's proposal, which closely followed the successful inauguration of the European Monetary Union, stirred interest throughout the Americas, particularly in Mexico and, a year later, in Ecuador. To some, dollarization in Mexico offered a guarantee against periodic peso devaluation and seemed a reasonable adjunct to the North American Free Trade Agreement. Others, howevel^, cited four years of relatively low exchange rate volatility and a reduction in the Mexican inflation rate as support for current arrangements: an independent central bank and a floating peso. Ecuador's President Jamil Mahuad announced his intentions to dollarize in January 2000 as a means of restoring monetary credibility to a battered economy. Although 80 percent of Ecuadorian assets are already dollar denominated, the decision prompted rioting. These events illustrate the importance of a perennial question in open-economy macroeconomics: What type of monetary and exchange rate arrangements best promote the economic welfare of a country? Robert Mundell (1961) first posed the question when he attempted to define an optimal currency area (OCA). His work produced a rich debate within the economics profession (Ishiyama 1975), but seemed to have only a tangential influence on the policy debates of the 1960s and 1970s a period of limited international capital mobility. As capital mobility in

Capturing downside risk in financial markets: the case of the Asian Crisis

Using data on Asian equity markets, we observe that during periods of financial turmoil, deviations from the mean-variance framework become more severe, resulting in periods with additional downside risk to investors. Current risk management techniques failing to take this additional downside risk into account will underestimate the true Value-at-Risk with greater severity during periods of financial turnoil. We provide a conditional approach to the Value-at-Risk methodology, known as conditional VaR-x, which to capture the time variation of non-normalities allows for additional tail fatness in the distribution of expected returns. These conditional VaR-x estimates are then compared to those based on the RiskMetrics™ methodology from J.P. Morgan, where we find that the model provides improved forecasts of the Value-at-Risk. We are therefore able to show that our conditional VaR-x estimates are better able to capture the nature of downside risk, particularly crucial in times of financial crises.