Stefan Straetmans

Asset Market Linkages in Crisis Periods

We characterize asset return linkages during periods of stress by an extremal dependence measure. Contrary to correlation analysis, this nonparametric measure is not predisposed toward the normal distribution and can allow for nonlinear relationships. Our estimates for the G-5 countries suggest that simultaneous crashes between stock markets are much more likely than between bond markets. However, for the assessment of financial system stability the widely disregarded cross-asset perspective is particularly important. For example, our data show that stock-bond contagion is approximately as frequent as flight to quality from stocks into bonds. Extreme cross-border linkages are surprisingly similar to national linkages, illustrating a potential downside to international financial integration.

Tail Behavior of Credit Loss Distributions for General Latent Factor Models

Using a limiting approach to portfolio credit risk, we obtain analytic expressions for the tail behavior of credit losses. To capture the co‐movements in defaults over time, we assume that defaults are triggered by a general, possibly non‐linear, factor model involving both systematic and idiosyncratic risk factors. The model encompasses default mechanisms in popular models of portfolio credit risk, such as CreditMetrics and CreditRisk+. We show how the tail characteristics of portfolio credit losses depend directly upon the factor models functional form and the tail properties of the models risk factors. In many cases the credit loss distribution has a polynomial (rather than exponential) tail. This feature is robust to changes in tail characteristics of the underlying risk factors. Finally, we show that the interaction between portfolio quality and credit loss tail behavior is strikingly different between the CreditMetrics and CreditRisk+ approach to modeling portfolio credit risk. Correspondence to: alucas@econ.vu.nl, pieter.klaassen@nl.abnamro.com, spreij@wins.uva.nl, or s.straetmans@berfin.unimaas.nl.

COMOVEMENTS OF DIFFERENT ASSET CLASSES DURING MARKET STRESS

This paper measures US financial asset class linkages (stocks, bonds, T-bills and gold) during crisis periods. We use extreme value analysis to assess the bivariate exposure of one asset class to extreme movements in the other asset classes. These bivariate co-crash probabilities can be interpreted as a measure of financial contagion. Statistical testing reveals that bivariate extreme linkage estimates exhibit time variation for certain asset pairs, possibly caused by exogenous factors like oil shocks or shifts in monetary policy. Our results have potentially important implications for long-run strategic asset allocation and pension fund management.

Fat tail distributions and local thin tail alternatives

The behaviour of the Hill estimator for the tail index of fat tailed distributions in the presence of local alternatives which have a thin tail is investigated. The converse problem is also briefly addressed. A local thin tail alternative can severely bias the Hill statistic. The relevance of this issue for the class of stable distributions is discussed. We conduct a small simulation study to support the analysis. In the conclusion it is argued that for moderate out of sample quantile analysis the problem of local alternatives may be less pressing.

Long-Term Asset Tail Risk in Developed and Emerging Markets

The tail of financial returns is typically governed by a power law (i.e. “fat tails”). However, the constancy of the so-called tail index α which dictates the tail decay has been hardly investigated. We study the finite sample properties of some recently proposed endogenous tests for structural change in α. Given that the finite sample critical values strongly depend on the tail parameters of the return distribution we propose a bootstrap-based version of the structural change test. Our empirical application spans a wide variety of long-term developed and emerging financial asset returns. Somewhat surprisingly, the tail behavior of emerging stock markets is not more strongly inclined to structural change than their developed counterparts. Emerging currencies, on the contrary, are more prone to shifts in the tail behavior than developed currencies. Our results suggest that extreme value theory (EVT) applications in hedging tail risks or in assessing the (changing) propensity to financial crises can assume stationary tail behavior over long time spans provided one considers portfolios that solely consist of stocks or bonds. However, our break results also indicate it is advisable to use shorter estimation windows when applying EVT methods to emerging currency portfolios.

Business and Financial Cycles in the Eurozone: Synchronization or Decoupling

This paper proposes a novel approach, based on probit framework, toward measuring bilateral synchronization, separately within business cycles and within financial cycles, for 11 eurozone economies. We find strong cross†country synchronization both within real cycles and within financial cycles. Moreover, financial cycle synchronization dominates business cycle synchronization in the eurozone, especially after the introduction of the single currency. For some peripheral country pairs, we even find some evidence of ‘decoupling’ of business cycles relative to the core countries but majority of marginal business cycle effects do not change much before and after the common currency. The former observation supports the plea for more Europe†wide macro†prudential regulation whereas the latter observation gives ammunition to those economists who always stress that the euro zone architecture is an unfinished business and that the conditions for an optimum currency area are not fulfilled.

Skewness Measures for the Weibull Distribution

The skewness of a statistical distribution is often used to determine whether that distribution is symmetric or not. Such a determination is misleading. To show this we have analyzed a broad range of (classes of) skewness measures – complying with the requirements of a general skewness measure – and applied the measures to the Weibull distribution. This distribution is known to be asymmetric for any value of its parameters. Nevertheless skewness measures might be equal to zero for a specific set of parameter values of the Weibull distribution, leading to the incorrect conclusion that the distribution is symmetric.Further, different general skewness measures might be zero for different values of the shape parameter (a) of the Weibull distribution, which makes it not possible to classify those distributions as being left- or right-skew. Consequently a Weibull distribution can be classified as being right-skew if a

Developed and Emerging Equity Market Tail Risk: Is it Constant?

The tail of equity returns is typically governed by a power law, however, the constancy of the so-called tail index α α , which dictates the tail decay, has been hardly studied. Using the Hill estimator to estimate the tail index, we study the finite sample properties of endogenous stability tests for α α . We show that the finite sample critical values strongly depend on the underlying distributional assumptions for the stock returns. We therefore recommend a bootstrap-based version of the stability test as an alternative to the test’s asymptotic distribution. Upon applying this stability test to return tails of developed and emerging equity markets, the evidence for structural shifts is found to be rather weak. This is reassuring news for the proponents of Extreme value Theory (EVT). They typically assume stationary tail behavior when applying tail index and extreme quantile estimators to the downside risk of equity portfolios.

Comovements of different asset classes during times of market stress

This paper measures US financial asset class linkages (stocks, bonds, T-bills and gold) during crisis periods. We use extreme value analysis to assess the bivariate exposure of one asset class to extreme movements in the other asset classes. These bivariate co-crash probabilities can be interpreted as a measure of financial contagion. Statistical testing reveals that bivariate extreme linkage estimates exhibit time variation for certain asset pairs, possibly caused by exogenous factors like oil shocks or shifts in monetary policy. Our results have potentially important implications for long-run strategic asset allocation and pension fund management.

COMOVEMENTS OF DIFFERENT ASSET CLASSES DURING MARKET STRESS: asset class linkages during market stress

This paper measures US financial asset class linkages (stocks, bonds, T-bills and gold) during crisis periods. We use extreme value analysis to assess the bivariate exposure of one asset class to extreme movements in the other asset classes. These bivariate co-crash probabilities can be interpreted as a measure of financial contagion. Statistical testing reveals that bivariate extreme linkage estimates exhibit time variation for certain asset pairs, possibly caused by exogenous factors like oil shocks or shifts in monetary policy. Our results have potentially important implications for long-run strategic asset allocation and pension fund management.