The Corona Recession and Bank Stress in Germany
Reint E. Gropp, Michael Koetter, William McShane
IWH Online,
No. 4,
2020
Abstract
We conduct stress tests for a large sample of German banks across different recoveries from the Corona recession. We find that, depending on how quickly the economy recovers, between 6% to 28% of banks could become distressed from defaulting corporate borrowers alone. Many of these banks are likely to require regulatory intervention or may even fail. Even in our most optimistic scenario, bank capital ratios decline by nearly 24%. The sum of total loans held by distressed banks could plausibly range from 127 to 624 billion Euros and it may take years before the full extent of this stress is observable. Hence, the current recession could result in an acute contraction in lending to the real economy, thereby worsening the current recession , decelerating the recovery, or perhaps even causing a “double dip” recession. Additionally, we show that the corporate portfolio of savings and cooperative banks is more than five times as exposed to small firms as that of commercial banks and Landesbanken. The preliminary evidence indicates small firms are particularly exposed to the current crisis, which implies that cooperative and savings banks are at especially high risk of becoming distressed. Given that the financial difficulties may seriously impair the recovery from the Covid-19 crisis, the pressure to bail out large parts of the banking system will be strong. Recent research suggests that the long run benefits of largely resisting these pressures may be high and could result in a more efficient economy.
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Banks’ Equity Performance and the Term Structure of Interest Rates
Elyas Elyasiani, Iftekhar Hasan, Elena Kalotychou, Panos K. Pouliasis, Sotiris Staikouras
Financial Markets, Institutions and Instruments,
No. 2,
2020
Abstract
Using an extensive global sample, this paper investigates the impact of the term structure of interest rates on bank equity returns. Decomposing the yield curve to its three constituents (level, slope and curvature), the paper evaluates the time-varying sensitivity of the bank’s equity returns to these constituents by using a diagonal dynamic conditional correlation multivariate GARCH framework. Evidence reveals that the empirical proxies for the three factors explain the variations in equity returns above and beyond the market-wide effect. More specifically, shocks to the long-term (level) and short-term (slope) factors have a statistically significant impact on equity returns, while those on the medium-term (curvature) factor are less clear-cut. Bank size plays an important role in the sense that exposures are higher for SIFIs and large banks compared to medium and small banks. Moreover, banks exhibit greater sensitivities to all risk factors during the crisis and postcrisis periods compared to the pre-crisis period; though these sensitivities do not differ for market-oriented and bank-oriented financial systems.
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12.03.2020 • 4/2020
Global economy under the spell of the coronavirus epidemic
The epidemic is obstructing the economic recovery in Germany. Foreign demand is falling, private households forgo domestic consumption if it comes with infection risk, and investments are postponed. Assuming that the spread of the disease can be contained in short time, GDP growth in 2020 is expected to be 0.6% according to IWH spring economic forecast. Growth in East Germany is expected to be 0.9% and thus higher than in West Germany. If the number of new infections cannot be decreased in short time, we expect a recession in Germany.
Oliver Holtemöller
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What Drives the Commodity-Sovereign-Risk-Dependence in Emerging Market Economies?
Hannes Böhm, Stefan Eichler, Stefan Gießler
Abstract
Using daily data for 34 emerging markets in the period 1994-2016, we find robust evidence that higher export commodity prices are associated with higher sovereign bond returns (indicating lower sovereign risk). The economic effect is especially pronounced for heavy commodity exporters. Examining the drivers, we find, first, that commodity-dependence is higher for countries that export large volumes of volatile commodities and that the effect increases in times of recessions, high inflation, and expansionary U.S. monetary policy. Second, the importance of raw material prices for sovereign financing can likely be mitigated if a country improves institutions and tax systems, attracts FDI inflows, invests in manufacturing, machinery and infrastructure, builds up reserve assets and opens capital and trade accounts. Third, the concentration of commodities within a country’s portfolio, its government indebtedness or amount of received development assistance appear to be only of secondary importance for commodity-dependence.
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A Factor-model Approach for Correlation Scenarios and Correlation Stress Testing
Natalie Packham, Fabian Wöbbeking
Journal of Banking and Finance,
April
2019
Abstract
In 2012, JPMorgan accumulated a USD 6.2 billion loss on a credit derivatives portfolio, the so-called “London Whale”, partly as a consequence of de-correlations of non-perfectly correlated positions that were supposed to hedge each other. Motivated by this case, we devise a factor model for correlations that allows for scenario-based stress testing of correlations. We derive a number of analytical results related to a portfolio of homogeneous assets. Using the concept of Mahalanobis distance, we show how to identify adverse scenarios of correlation risk. In addition, we demonstrate how correlation and volatility stress tests can be combined. As an example, we apply the factor-model approach to the “London Whale” portfolio and determine the value-at-risk impact from correlation changes. Since our findings are particularly relevant for large portfolios, where even small correlation changes can have a large impact, a further application would be to stress test portfolios of central counterparties, which are of systemically relevant size.
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Drivers of Systemic Risk: Do National and European Perspectives Differ?
Claudia M. Buch, Thomas Krause, Lena Tonzer
Journal of International Money and Finance,
March
2019
Abstract
With the establishment of the Banking Union, the European Central Bank has been granted the power to impose stricter regulations than the national regulator if systemic risks are not adequately addressed at the national level. We ask whether there is a cross-border externality in the sense that a bank’s systemic risk differs when applying a national versus a European perspective. On average, banks’ contribution to systemic risk is similar at the two regional levels, and so is the ranking of banks. Generally, larger banks and banks with a lower share of loans are more systemically important. The effects of these variables are qualitatively but not quantitatively similar at the national versus the European level.
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How Do Banks React to Catastrophic Events? Evidence from Hurricane Katrina
Claudia Lambert, Felix Noth, Ulrich Schüwer
Review of Finance,
No. 1,
2019
Abstract
This paper explores how banks react to an exogenous shock caused by Hurricane Katrina in 2005, and how the structure of the banking system affects economic development following the shock. Independent banks based in the disaster areas increase their risk-based capital ratios after the hurricane, while those that are part of a bank holding company on average do not. The effect on independent banks mainly comes from the subgroup of highly capitalized banks. These independent and highly capitalized banks increase their holdings in government securities and reduce their total loan exposures to non-financial firms, while also increasing new lending to these firms. With regard to local economic development, affected counties with a relatively large share of independent banks and relatively high average bank capital ratios show higher economic growth than other affected counties following the catastrophic event.
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Too Connected to Fail? Inferring Network Ties from Price Co-movements
Jakob Bosma, Michael Koetter, Michael Wedow
Journal of Business and Economic Statistics,
No. 1,
2019
Abstract
We use extreme value theory methods to infer conventionally unobservable connections between financial institutions from joint extreme movements in credit default swap spreads and equity returns. Estimated pairwise co-crash probabilities identify significant connections among up to 186 financial institutions prior to the crisis of 2007/2008. Financial institutions that were very central prior to the crisis were more likely to be bailed out during the crisis or receive the status of systemically important institutions. This result remains intact also after controlling for indicators of too-big-to-fail concerns, systemic, systematic, and idiosyncratic risks. Both credit default swap (CDS)-based and equity-based connections are significant predictors of bailouts. Supplementary materials for this article are available online.
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Information Feedback in Temporal Networks as a Predictor of Market Crashes
Stjepan Begušić, Zvonko Kostanjčar, Dejan Kovač, Boris Podobnik, H. Eugene Stanley
Complexity,
September
2018
Abstract
In complex systems, statistical dependencies between individual components are often considered one of the key mechanisms which drive the system dynamics observed on a macroscopic level. In this paper, we study cross-sectional time-lagged dependencies in financial markets, quantified by nonparametric measures from information theory, and estimate directed temporal dependency networks in financial markets. We examine the emergence of strongly connected feedback components in the estimated networks, and hypothesize that the existence of information feedback in financial networks induces strong spatiotemporal spillover effects and thus indicates systemic risk. We obtain empirical results by applying our methodology on stock market and real estate data, and demonstrate that the estimated networks exhibit strongly connected components around periods of high volatility in the markets. To further study this phenomenon, we construct a systemic risk indicator based on the proposed approach, and show that it can be used to predict future market distress. Results from both the stock market and real estate data suggest that our approach can be useful in obtaining early-warning signals for crashes in financial markets.
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