Nikola A. Tarashev

Attributing Systemic Risk to Individual Institutions

An operational macroprudential approach to financial stability requires tools that attribute system-wide risk to individual institutions. Making use of constructs from game theory, we propose an attribution methodology that has a number of appealing features: it can be used in conjunction with popular risk measures, it provides measures of institutions’ systemic importance that add up exactly to the measure of system-wide risk and it easily accommodates uncertainty about the validity of the risk model. We apply this methodology to a number of constructed examples and illustrate the interactions between drivers of systemic importance: size, the institution’s risk profile and strength of exposures to common risk factors. We also demonstrate how the methodology can be used for the calibration of macroprudential capital rules.

An Empirical Evaluation of Structural Credit Risk Models

This paper evaluates empirically the performance of six structural credit risk models by comparing the probabilities of default (PDs) they deliver to ex post default rates. In contrast to previous studies pursuing similar objectives, the paper employs firm-level data and finds that theory-based PDs tend to match closely the actual level of credit risk and to account for its time path. At the same time, nonmodelled macro variables from the financial and real sides of the economy help to substantially improve the forecasts of default rates. The finding suggests that theory-based PDs fail to fully reflect the dependence of credit risk on the business and credit cycles. Most of the upbeat conclusions regarding the performance of the PDs are due to models with endogenous default. For their part, frameworks that assume exogenous default tend to underpredict credit risk. Three borrower characteristics influence materially the predictions of the models: the leverage ratio; the default recovery rate; and the risk-free rate of return.

Measuring Portfolio Credit Risk Correctly: Why Parameter Uncertainty Matters

Why should risk management systems account for parameter uncertainty? In order to answer this question, this paper lets an investor in a credit portfolio face non-diversifiable estimation-driven uncertainty about two parameters: probability of default and asset-return correlation. Bayesian inference reveals that - for realistic assumptions about the portfolios credit quality and the data underlying parameter estimates - this uncertainty substantially increases the tail risk perceived by the investor. Since incorporating parameter uncertainty in a measure of tail risk is computationally demanding, the paper also derives and analyzes a closed-form approximation to such a measure.

Modelling and Calibration Errors in Measures of Portfolio Credit Risk

This paper develops an empirical procedure for analyzing the impact of model misspecification and calibration errors on measures of portfolio credit risk. When applied to large simulated portfolios with realistic characteristics, this procedure reveals that violations of key assumptions of the well-known Asymptotic Single-Risk Factor (ASRF) model are virtually inconsequential. By contrast, flaws in the calibrated interdependence of credit risk across exposures, which are driven by plausible small-sample estimation errors or popular rule-of-thumb values of asset return correlations, can lead to significant inaccuracies in measures of portfolio credit risk. Similar inaccuracies arise under erroneous, albeit standard, assumptions regarding the tails of the distribution of asset returns.

The Pricing of Correlated Default Risk: Evidence from the Credit Derivatives Market

In order to analyze the pricing of portfolio credit risk - as revealed by tranche spreads of a popular credit default swap (CDS) index - we extract risk-neutral probabilities of default (PDs) and physical asset return correlations from single-name CDS spreads. The time profile and overall level of index spreads validate our PD measures. At the same time, the physical asset return correlations are too low to account for the spreads of index tranches and, thus, point to a large correlation risk premium. This premium, which co-varies negatively with current realized correlations and positively with future realized correlations, sheds light on market perceptions of and attitude towards correlation risk.

The Pricing of Portfolio Credit Risk

Equity and credit-default-swap (CDS) markets are in disagreement as to the extent to which asset returns co-move across firms. This suggests market segmentation and casts ambiguity about the asset-return correlations underpinning observed prices of portfolio credit risk. The ambiguity could be eliminated by – currently unavailable – data that reveal the market valuation of low-probability/large-impact events. At present, judicious assumptions about this valuation can be used to reconcile observed prices with asset-return correlations implied by either equity or CDS markets. These conclusions are based on an analysis of tranche spreads of a popular CDS index, which incorporate a rather small premium for correlation risk.

Are speculative attacks triggered by sunspots? A new test

The empirical methodology of the paper establishes if a speculative attack, which is accounted for via sunspots in the presence of multiple equilibria, could have been in fact driven uniquely by economic fundamentals. The methodology is based on the theoretical models of Bertola and Svensson (1993) and Tarashev (2003). The first model captures robust stylised facts from target zone regimes, whereas the second one implies that both unique and multiple equilibria can account for violent speculative attacks. The characteristics of the theoretical foundations and their implications for the employed statistical test distinguish the paper from previous structural empirical analyses of market bets against pegged currencies. The methodology is applied to the experience of two ERM countries in the fall of 1992. The attack on the French Franc is found to be triggered by sunspots, whereas it is impossible to determine whether a similar scenario or the state of the economy alone underpins the currency crisis in Italy.