Niklas Wagner

Government Intervention in Response to the Subprime Financial Crisis: The Good into the Pot, the Bad into the Crop

The subprime-related 2007/2008 global financial crisis represented a major economic challenge. In order to prevent such episodes of market failure, it is vital to understand what caused the crisis and which lessons are to be learned. Given the tremendous bailout packages worldwide, we discuss the role of governments as lenders of last resort. In our view, it is important not to suspend the market mechanism of bankruptcy via granting rescue packages. Only those institutions which are illiquid but solvent should be rescued, and this should occur at a significant cost for the respective institution. We provide a formal illustration of a rescue mechanism, which allows to distinguish between illiquid but solvent and insolvent banks. Furthermore, we argue that stricter regulation cannot be the sole consequence of the crisis. There appears to be a need for improved risk awareness, more sophisticated risk management and a better alignment of interests among the participants in the market for credit risk.

Measuring tail thickness under GARCH and an application to extreme exchange rate changes

Accurate modeling of extreme price changes is vital to financial risk management. We examine the small sample properties of adaptive tail index estimators under the class of student-t marginal distribution functions including GARCH and propose a model-based bias-corrected estimation approach. Our simulation results indicate that bias strongly relates to the underlying model and may be positively as well as negatively signed. The empirical study of daily exchange rate changes reveals substantial differences in measured tail-thickness due to small sample bias. As a consequence, high quantile estimation may lead to a substantial underestimation of tail risk.

Surprise volume and heteroskedasticity in equity market returns

Heteroskedasticity in returns may be explainable by trading volume. We use different volume variables, including surprise volume—i.e. unexpected above-average trading activity—which is derived from uncorrelated volume innovations. Assuming weakly exogenous volume, we extend the Lamoureux and Lastrapes (1990) model by an asymmetric GARCH in-mean specification following Golsten et al. (1993). Model estimation for the US as well as six large equity markets shows that surprise volume provides superior model fit and helps to explain volatility persistence as well as excess kurtosis. Surprise volume reveals a significant positive market risk premium, asymmetry and a surprise volume effect in conditional variance. The findings suggest that e.g. a surprise volume shock (breakdown)—i.e. large (small) contemporaneous and small (large) lagged surprise volume—relates to increased (decreased) conditional market variance and return.

Estimating financial risk under time-varying extremal return behavior

Abstract. Potentially increasing volatility and downside risk is essential to financial risk management which is concerned with the tails, or particularly, the lower tail, of the distribution of speculative asset returns. Applying extreme value theory, the present paper outlines a simple model capturing time-varying tail behavior and studies conditional daily return quantiles for the German DAX. Our results indicate an overall increased risk of large one-day holding-period losses related to a structural break given by the 1987 crash, systematic out-of-sample underestimation of the magnitude of extreme quantiles as well as clustering in estimated quantile exceedances which cannot be fully explained by the forecasting model.

Equities, credits and volatilities: A multivariate analysis of the European market during the subprime crisis

We study the lead–lag dependence between aggregate credit spreads and equity prices as well as implied equity volatility, which is important for proper credit risk assessment. Our analysis includes daily quotes of the iTraxx Europe index, the Dow Jones Euro Stoxx 50 index, and the Dow Jones VStoxx index during the period of June 2004 to April 2009, i.e. before and during the subprime financial crisis. We robustly estimate a vector autoregressive (VAR) model, allow for time-varying coefficients and assume a multivariate autoregressive conditional heteroskedastic (ARCH) model of the BEKK-type for the innovations. We find that while the commonly predicted negative relation between asset prices and credit spreads holds during the pre-crisis period, it fails to hold during the subsequent crisis period. Equity returns turn out to be insignificant predictors of spreads during the crisis and spread changes significantly and positively lead changes in equity market volatility. Hence, while information in aggregate spreads is typically not driving aggregate market risk, it well may do so during a period in which severe stress in credit markets spills over to the equity market. In sum our results cast some doubt on the stability of the predictions of structural models of credit risk during periods of market stress.

Interest Rates, Stock Returns and Credit Spreads: Evidence from German Eurobonds

We investigate daily variations in credit spreads on investment-grade Deutschemark-denominated Eurobonds during the challenging 1994-1998 period. Empirical results from a Longstaff and Schwartz (1995) two-factor regression, extended for correlated spread changes and heteroskedasticity, indicate strong persistence in spread changes. Consistent with theory and previous findings, changes in spreads are significantly negatively related to the term-structure level while, contrary to theory, the proxy for asset value does not yield a significant negative contribution. We even find a significant positive relation for Eurobonds with long maturity. Tentative interpretations are portfolio-rebalancing activities or differing risk factor sensitivities on short- vs. long-maturity bonds. Copyright Banca Monte dei Paschi di Siena SpA, 2005

Tail index estimation in small smaples Simulation results for independent and ARCH-type financial return models

Estimation of the tail index of stationary, fat-tailed return distributions is non-trivial since the well-known Hill estimator is optimal only under iid draws from an exact Pareto model. We provide a small sample simulation study of recently suggested adaptive estimators under ARCH-type dependence. The Hill estimator’s performance is found to be dominated by a ratio estimator. Dependence increases estimation error which can remain substantial even in larger data sets. As small sample bias is related to the magnitude of the tail index, recent standard applications may have overestimated (underestimated) the risk of assets with low (high) degrees of fat-tailedness.

On Adaptive Tail Index Estimation for Financial Return Models

Estimation of the tail index of stationary, fat-tailed return distributions is non-trivial since the well-known Hill estimator is optimal only under iid draws from an exact Pareto model. We provide a small sample simulation study of recently suggested adaptive estimators under ARCH-type dependence. The Hill estimators performance is found to be dominated by a ratio estimator. Dependence increases estimation error which can remain substantial even in larger data sets. As small sample bias is related to the magnitude of the tail index, recent standard applications may have overestimated (underestimated) the risk of assets with low (high) degrees of fat-tailedness.

Modeling the Cash Flow Dynamics of Private Equity Funds: Theory and Empirical Evidence

This article presents a novel continuous-time approach to modeling the typical cash flow dynamics of private equity funds. The model consists of two independent components. First is a mean-reverting square-root process applied to model the rate at which capital is drawn over time. Second is the stream of capital distributions, which is assumed to follow an arithmetic Brownian motion with a time-dependent drift component that incorporates the typical time-pattern of the repayments of private equity funds. The empirical analysis shows that the model can easily be calibrated to real-world fund data by the method of conditional least squares and nicely fits historical data. The authors use a data set of mature European private equity funds provided by Thomson Venture Economics. Their model explains up to 99.6% of the variation in average cumulated net fund cash flows and provides a good approximation of the empirical distribution of private equity fund cash flows over a typical fund’s lifetime. Overall, the empirical results indicate that the model is of economic relevance in an effort to accurately model the cash flow dynamics of private equity funds.

Quantitative Easing and the Pricing of EMU Sovereign Debt

We study the pricing of EMU sovereign debt by a novel panel regression approach. This allows us to consider a comprehensive set of observable explanatory variables jointly with additional unobservable time-varying common factors. We add to the existing literature by considering the pricing effects of conventional as well as unconventional monetary policy and by controlling for possible variance risk premium effects. During the European sovereign debt crisis, unconventional monetary policy is found to have a pronounced spread decreasing effect, where policy elasticity is about three times larger than prior to the crisis. Furthermore, a rise in the variance risk premium significantly relates to spread increases. During the overall sample period, changes in country-specific bond market liquidity as well as aggregate market liquidity both help to explain yield spread variations. Three time-varying common factors account for about two-thirds of the variation in yield spread changes. The major component is a systematic risk factor, which captures a time-varying risk premium. The remainder factors help to explain bond valuations prior to and during the debt crisis.