Systemic liquidity contagion in the European interbank market

Systemic liquidity risk, defined by the International Monetary Fund as “the risk of simultaneous liquidity difficulties at multiple financial institutions,” is a key topic in financial stability studies and macroprudential policy-making. In this context, the complex web of interconnections of the interbank market plays the crucial role of allowing funding liquidity shortages to propagate between financial institutions. Here, we introduce a simple yet effective model of the interbank market in which liquidity shortages propagate through an epidemic-like contagion mechanism on the network of interbank loans. The model is defined by using aggregate balance sheet information of European banks, and it exploits country and bank-specific risk features to account for the heterogeneity of financial institutions. Moreover, in order to obtain the European-wide topology of the interbank network, we define a block reconstruction method based on the exchange flows between the various countries. We show that the proposed contagion model is able to estimate systemic liquidity risk across different years and countries. Results suggest that our effective contagion approach can be successfully used as a viable alternative to more realistic but complicated models, which not only require more specific balance sheet variables with high time resolution but also need assumptions on how banks respond to liquidity shocks.

     

Forecasting distress in cooperative banks: The role of asset quality

This paper analyzes the drivers of financial distress that were experienced by small Italian cooperative banks during the latest deep recession, focusing mainly on the importance of bank capital as a predictor of bankruptcy for Italian nonprofit banks. The analysis aims to build an early-warning model that is suitable for this type of bank.The results reveal non-monotonic effects of bank capital on the probability of failure. In contrast to distress models for for-profit banks, non-performing loans, profitability, liquidity, and management quality have a negligible predictive value. The findings also show that unreserved impaired loans have an important impact on the probability of bank distress. Moreover, the loan–loss ratio provision on substandard loans constitutes a suitable antibody against bank distress. Overall, the results are robust in terms of both the methodology (i.e., frequentist and Bayesian approaches) and the sample used (i.e., cooperative banks in Italy and euro-area countries).     

Firms in financial distress: evidence from inter-firm payment networks with volatility driven by ‘animal spirits’

This paper elaborates an agent-based model of a pure market economy to provide theoretical evidence on how volatility-induced changes in inter-firm payment networks affect the financial distress of firms. This volatility is driven by ‘animal spirits’ in that it arises from the feelings of optimism/pessimism independently of rational decision-making, and influences the liquidity available to each firm through the inter-firm payment network; consequently, some firms may enter financial distress. The model first determines the inter-firm payment network. Then, a mean-reverting square-root process introduces volatility into the inter-firm payment network through firms’ propensity to pay suppliers according to the payments that firms expect to receive from customers. The model is calibrated for compatibility with relevant macro- and microeconomic stylized facts. According to computational experiments, financial distress in the business sector is minimized when feelings of optimism/pessimism generate the lowest volatility in firms’ propensity to pay suppliers. In addition, this volatility must materialize around an intermediate value of firms’ propensity to pay suppliers, and firms must keep this intermediate value over time.

     

Risk contagion in the banking network: New evidence from China

Based on data from 111 Chinese banks over the 2013–2016 period, this paper estimates the interbank bilateral lending matrix using the maximum entropy method. The estimated matrix is used to simulate the effects of credit and liquidity shocks on China’s banking network. Simulation results show that, under the extreme pressure scenario, the contagion arising from a liquidity shock is significantly stronger than the effect of a credit shock, indicating the importance of liquidity in the banking system. The contagion effect arising from a credit shock does not vary much over the sample period. However, the contagion effect arising from a liquidity shock decreases significantly, which could be attributed to contraction in interbank business due to stricter interbank business supervision. The simulation results also identify the most important and most vulnerable nodes of the banking system. An increase in the level of capital level can enhance the ability of banks to withstand credit and liquidity shocks. Our analysis also suggests that risk contagion faced by China’s banks varies across banking network structures.     

A model of the topology of the bank – firm credit network and its role as channel of contagion

This paper proposes a stochastic model of a bipartite credit network between banks and the non-bank corporate sector that encapsulates basic stylized facts found in comprehensive data sets for bank-firm loans for a number of countries. When performing computational experiments with this model, we find that it shows a pronounced non-linear behavior under shocks: the default of a single unit will mostly have practically no knock-on effects, but might lead to an almost full-scale collapse of the entire system in a certain number of cases. The dependency of the overall outcome on firm characteristics like size or number of loans seems fuzzy. Distinguishing between contagion due to interbank credit and due to joint exposures to counterparty risk via loans to firms, the later channel appears more important for contagious spread of defaults.     

The impact of funding liquidity on market quality

This study analyzes market quality during the 2007–2008 credit crunch, by examining the impact of funding liquidity on market liquidity and price discovery of S&P 500 exchange-traded funds (i.e., S&P 500 depositary receipts [SPYs]) and index futures (E-minis). The empirical results show that funding liquidity affects market liquidity, and that the impact of illiquidity contagion between SPYs and E-minis was significant during the subprime mortgage crisis. In particular, the contagion effects between the two markets mediate the impact of funding illiquidity on market liquidity during the credit crunch. Considering the influences of other market factors on price discovery, we suggest that E-mini index futures made less contributions to price discovery during the credit crunch compared to normal periods. The empirical finding emphasizes the importance of the contagion effect between ETF and E-mini futures markets, when they suffer from external shocks.     

Contagion risk in the Czech financial system: A network analysis and simulation approach

This paper examines the potential for contagion within the Czech banking system via the channel of interbank exposures of domestic banks, enriched by a liquidity channel and an asset price channel, over the period March 2007 to June 2012. A computational model is used to assess the resilience of the Czech banking system to interbank contagion, taking into account the size and structure of interbank exposures as well as balance sheet and regulatory characteristics of individual banks in the network. The simulation results suggest that the potential for contagion due to credit losses on interbank exposures was rather limited. Even after the introduction of a liquidity condition into the simulations, the average contagion was below 3.8% of the remaining banking sector assets, with the exception of the period from December 2007 to September 2008. Activation of the asset price channel further increases the losses due to interbank contagion, showing that the liquidity of government bonds would be essential for the stability of Czech banks in stress situations. Finally, the simulation results for both idiosyncratic and multiple bank failure shocks suggest that the potential for contagion in the Czech banking system has decreased since the onset of the global financial crisis.     

Too dynamic to fail: empirical support for an autocatalytic model of Minsky’s financial instability hypothesis

Solomon and Golo (Account Econ Law 3(3):167–260, 2013) have recently proposed an autocatalytic (self-reinforcing) feedback model which couples a macroscopic system parameter (the interest rate), a microscopic parameter that measures the distribution of the states of the individual agents (the number of firms in financial difficulty) and a peer-to-peer network effect (contagion across supply chain financing). In this model, each financial agent is characterized by its resilience to the interest rate. Above a certain rate the interest due on the firm’s financial costs exceeds its earnings and the firm becomes susceptible to failure (ponzi). For the interest rate levels under a certain threshold level, the firm loans are smaller then its earnings and the firm becomes ‘hedge.’ In this paper, we fit the historical data (2002–2009) on interest rate data into our model, in order to predict the number of the ponzi firms. We compare the prediction with the data taken from a large panel of Italian firms over a period of 9 years. We then use trade credit linkages to discuss the connection between the ponzi density and the network percolation. We find that the ‘top-down’–‘bottom-up’ positive feedback loop accounts for most of the Minsky crisis accelerator dynamics. The peer-to-peer ponzi companies contagion becomes significant only in the last stage of the crisis when the ponzi density is above a critical value. Moreover the ponzi contagion is limited only to the companies that were not dynamic enough to substitute their distressed clients with new ones. In this respect the data support a view in which the success of the economy depends on substituting the static ‘supply-network’ picture with an interacting dynamic agents one.     

Firm-specific,industry-specific and macroeconomic factors of life insurers’ profitability: Evidence from Canada

The purpose of this study is to examine the effects of firm-specific, industry-specific and macroeconomic factors on the performance of life insurance firms. This study focuses on the Canadian life insurance sector, which is the second largest and oldest financial services sector in Canada. Using an empirical framework that incorporates both fixed and dynamic panel models that control for endogeneity issues, this research finds that size, liquidity, and risk exposure of life insurers are significant factors in their profitability. Secondly, industry concentration (e.g., HHI) fail to provide any meaningful evidence to support the structure-conduct-performance (SCP) theory in the static panel models, but in the dynamic models, industry concentration tends to have negative impacts on profitability. Macroeconomic factors such as real GDP growth and equity market returns are found to be significant determinants of insurers’ profitability. Finally, the persistence of profits for life insurers’ seems to lag that of their financial services counterparts (e.g., banks).     

A survey of network-based analysis and systemic risk measurement

The financial crisis led to a number of new systemic risk measures and a renewed concern over the risk of contagion. This paper surveys the systemic risk literature with a focus on the importance of contributions made by those emphasizing a network-based approach, and how that compares with more commonly used approaches. Research on systemic risk has generally found that the risk of contagion through domino effects is minimal, and thus emphasized focusing on the resiliency of the financial system to broad macroeconomic shocks. Theoretical, methodological, and empirical work is critically examined to provide insight on how and why regulators have emphasized deregulation, diversification, size-based regulations, and portfolio-based coherent systemic risk measures. Furthermore, in the context of network analysis, this paper reviews and critically assesses newly created systemic risk measures. Network analysis and agent-based modeling approaches to understanding network formation offer promise in helping understand contagion, and also detecting fragile systems before they collapse. Theory and evidence discussed here implies that regulators and researchers need to gain an improved understanding of how topology, capital requirements, and liquidity interact.     

Cross-sectional differences in the liquidity effects of open market share repurchases

I examine liquidity changes associated with open market share repurchases, with the focus on potential cross-sectional variations of liquidity effects. I hypothesize that a liquidity change, either a decrease or an increase, will be larger in a firm with a higher degree of pre-announcement information asymmetry. Results suggest that the null hypothesis of no liquidity change cannot be rejected. In particular, there is no evidence for cross-sectional variation of liquidity changes across firms with differing degrees of information asymmetry. Special/thanks go to Kim Woo Choong, former chairman of DAEWOO Group, and Park Chung Kil for their support.     

Forecasting and explaining aggregate consumer credit delinquency behaviour

We model aggregate delinquency behaviour for consumer credit (including credit card loans and other consumer loans) and for residential real estate loans using data up until 2008. We test for cointegrating relationships and then estimate short run error correction models. We find evidence to support the portfolio explanations of declines in credit quality for consumer and for real estate loans, but support for the reduced stigma explanation was restricted to real estate loans. Evidence supportive of household-level explanations of irrational borrowing and unexpected net income shocks was found for consumer and real estate loans, but evidence of strategic default was restricted to the volume of consumer loans and real estate loans, and not for credit cards. We also found that the error correction model gave forecasts of the volume of delinquent consumer debt which were of an accuracy comparable to that of an ARIMA model.     

Does a central clearing counterparty reduce liquidity needs?

This study investigates whether and how central clearing influences the overall liquidity needs in a network of financial obligations. Utilizing the approach of flow network theory, we show that the effect of adding a central clearing counterparty (CCP) is decomposed into two effects: central routing, and central netting effects. Each effect can produce different liquidity needs according to different liquidity scenarios. The analysis indicates that adding a CCP in times of financial distress successfully reduces the overall liquidity needs if and only if the netting efficiency of the CCP is sufficiently high. Furthermore, once the economy is no longer in financial distress, higher netting efficiency of the CCP could conversely increase the overall liquidity needs. The results have implications for the effectiveness of CCPs in mitigating systemic risk in times of financial distress, and their operating costs once the distress has passed.     

Labor's liquidity service and firing costs

This paper studies the specific effect that firing costs can have on firms facing liquidity constraints. When firing costs are zero and a time gap exists between production and its associated revenues, firing allows firms to hold on to their liquid assets by saving on wages, and thus, allows firms to cope better with liquidity shocks when external financing is too costly or unavailable. I refer to this feature as labor's liquidity service. Higher firing costs reduces the value of labor's liquidity service, and thus, increases firms' incentive for hoarding liquidity and reduces firms' demand for production inputs. In addition to this negative effect at the creation margin of production, firing costs have a relatively higher positive effect on the destruction margin of production of financially restricted firms. This paper presents a model that develops these ideas and shows that the presence of firing costs has a stronger negative effect on the output of firms facing liquidity constraints. Regression analysis, based on country-industry panel data sets, provides empirical evidence consistent with the liquidity service effect of firing costs. I find a relatively stronger negative effect of firing costs on the output of industries with higher liquidity requirements and a relatively stronger negative effect of firing costs on the output of small, and more likely financially constrained, firms.     

The number of banking relationships and the business cycle: New evidence from Colombia

We study the determinants of multiple bank–firm relationships using a uniquely rich data set comprised of information on individual loans of a large number of firms in Colombia. We control for firm-specific variables and find that the business cycle exerts important influence on the number of bank relationships sustained by firms. Our evidence suggests that the number of bank relationships is counter-cyclical, decreasing during macroeconomic expansions and increasing during contractions. However, this effect is stronger for large firms which have more access to alternative sources of funding.     

The duality of bankruptcy process in Finland

Standard bankruptcy prediction methods lead to models weighted by the types of failure firms included in the estimation sample. These kinds of weighted models may lead to severe classification errors when they are applied to such types of failing (and non-failing) firms which are in the minority in the estimation sample (frequency effect). The purpose of this study is to present a bankruptcy prediction method based on identifying two different failure types, i.e. the solidity and liquidity bankruptcy firms, to avoid the frequency effect. Both of the types are depicted by a theoretical gambler's ruin model of its own to yield an approximation of failure probability separately for both types. These models are applied to the data of randomly selected Finnish bankrupt and non-bankrupt firms. A logistic regression model based on a set of financial variables is used as a benchmark model. Empirical results show that the resulting heavily solidity-weighted logistic model may lead to severe errors in classifying non-bankrupt firms. The present approach will avoid these kinds of error by separately evaluating the probability of the solidity and liquidity bankruptcy; the firm is not classified bankrupt as long as neither of the probabilities exceeds the critical value. This leads the present prediction method slightly to outperform the logistic model in the overall classification accuracy.     

Does audit report information improve financial distress prediction over Altman's traditional Z‐Score model?

We analyze empirically the usefulness of combining accounting and auditing data in order to predict corporate financial distress. Concretely, we examine whether audit report information incrementally predicts distress over a traditional accounting model: the Altman's Z‐Score model. Although the audit report seems to play a critical part in financial distress prediction because auditors should warn investors about any default risks, this is the first study that uses audit report disclosures for predicting purposes. From a dataset of 1,821 Spanish distressed private firms, we analyze a sample of distressed and non‐distressed firms and develop logit prediction models. Our results show that while the only accounting model registers a classification accuracy of 77%, combined models of accounting and auditing data exhibit considerably higher accuracy (about 87%). Specifically, our findings indicate that the number of disclosures included in the audit report, as well as disclosures related to a firm's going concern status, firms’ assets, and firms’ recognition of revenues and expenses contribute the most to the prediction. Our empirical evidence has implications for financial distress practice. For managers, our study highlights the importance of audit report disclosures for anticipating a financial distress situation. For regulators and auditors, our study underscores the importance of recent changes in regulation worldwide intended to increase auditor's transparency through a more informative audit report.     

An analysis of non-financial factors associated with financial distress

This article examines factors associated with financial distress among 1006 Spanish manufacturings (SMEs), distinguishing high and low technology industries. Financial distress is analysed using industrial organizational theory through the Porter's five competitive forces model (external factors) and the resource based view through strategic variables (internal factors), such as training, planning, innovation, technology and quality. Two different sources of information were used in the study: Qualitative information related to environmental conditions and strategic variables was gathered through a questionnaire addressed to the firm manager. Quantitative information to identify whether the firm was in financial distress was gathered from the balance sheets and earning statements of the firms. Evidence from this study shows that environmental conditions and some strategic variables are associated with financial distress. The results found that young SMEs with low technology and in a highly competitive environment had a higher probability of financial distress. High bargaining power of buyers and high degree of rivalry among existing competitors were positively associated with financial distress. Financial distress in high-technology industries was not affected by external factors. However, firms with a quality certification have better quality control procedures that ultimately improve financial performance of firms in the technology industries.     

Do voluntary disclosures of bad news improve liquidity?

Can managers improve market liquidity and lower the cost of capital by providing voluntary earnings guidance? This study examines the impact of profit warnings on market liquidity and finds that voluntary disclosure of bad news actually improves market liquidity. By conducting an empirical study over the period 1995–2010 on NYSE, NASDAQ and AMEX listed firms, we find that firms that issue profit warnings show enhanced market liquidity during the post-announcement period. We show that profit warnings reduce information asymmetry and lower bid-ask spreads and increase trading volumes. These results are invariant to daily (short run) and monthly (long run) data after controlling for firm specific attributes. The results have major corporate policy implications. By voluntarily disclosing negative earnings guidance by managers, firms will experience significant improvement in market liquidity, thereby lowering the cost of capital. Our results are even more profound for firms that release bad news with extremely negative stock market impact. In other words, voluntary disclosure of bad news is good for market liquidity.     

Dynamic credit contagion and aggregate loss in networks

We develop a dynamic model to illustrate the credit risk contagion mechanism caused by interaction between firms. Specifically, we formulate the sources of risk into idiosyncratic risk and contagion risk, and introduce recovery ability to model the scenario of a firm changing from default into normal status. Our result shows that there always exists a steady state in a network under some trivial conditions. For quasi-regular networks and bipartite networks, the expected aggregate loss remains unchanged as long as the product of the contagion probability and the partner number is fixed.