Credit Risk in a Network Economy

We develop a structural model of credit risk in a network economy. In particular, we are able to account for complex counterparty relationships,where one company may be indirectly affected by the credit risk of another company in the network. In this re-spect,we generalize Jarrow and Yu (2001)and Collin-Dufresne,Goldstein and Hugonnier (2003),but do so in the rich context of a structural form model. We provide closed form formulae for the price of risky debt and equity,which depend upon the lending/borrowing relationships in the economy. Our model applies to completely general lender/borrower relationships,including looping relationships. Our formulae can apply to cases where not only ?nancial ?ows but also operations are dependent across ?rms. In order to achieve these results,we use queueing theory. This paper thus represents one of the ?rst applications of queueing theory to ?nance.Credit Risk; Capital Structure; Queueing Networks

The effects of interbank networks on efficiency and stability in a macroeconomic agent-based model

We develop a macroeconomic agent-based model that consists of firms, banks, unions and households who interact on labour, goods, credit and interbank markets. The model endogenises pricing decisions by firms, wage setting by unions and interest rate setting by banks on both firm and interbank lending. Banks also set leverage targets and precautionary liquidity buffers on the basis of internal risk models. Our model produces endogenous fluctuations driven by the pricing behaviour of firms and the wage setting behaviour of unions. Fluctuations lead to loan defaults which are exacerbated as lenders reduce lending and charge higher interest rates, inducing a credit crunch. We also study how making the inter-banking network more connected affects the key outcomes of the economy and find that while the flow of funds from surplus banks to firms can be increased, the latter effect is soon dominated by increasing instability in the real sector as firms default at higher rates. While the banking sector experiences fewer defaults as a whole, losses on the interbank market increase as a source of bank defaults

Liquidity-saving through obligation-clearing and mutual credit: an effective monetary innovation for SMEs in times of crisis

During financial crises, liquidity tends to become scarce, a problem that disproportionately affects small companies. This paper shows that obligation-clearing is a very effective liquidity-saving method for providing relief in the trade credit market and, therefore, on the supply-side or productive part of the economy. The paper also demonstrates that when used in conjunction with a complementary currency system such as mutual credit as a liquidity source the effectiveness of obligation-clearing can be doubled. Real data from the Sardex mutual credit system show a reduction of net internal debt of the obligation network of approximately 25% when obligation-clearing is used by itself and of 50% when it is used together with mutual credit. These instruments are also relevant from the point of view of risk mitigation for lenders, based in part on the information on individual companies that the mutual credit circuit manager can provide to banks (upon the circuit member’s request) and in part on the relief that liquidity-saving provides especially to NPL companies. The paper concludes by outlining recommendations for how even greater savings could be achieved by including the tax authority as another node in the obligation network

Risky Business: The Credit Crisis and Failure (Part I)

The credit crisis represents a watershed event for global financial markets and has been linked to significant declines in real economy performance on a level of magnitude not experienced since World War II. Recognition of the crisis in 2008 has been followed in 2009 and 2010 by a plethora of competing proposals in response to the credit crisis. The result has been a cacophony of visions, voices, and approaches. The sheer noise that has ensued threatens to drown out the fundamental core questions that should be asked about the credit crisis. Among the most important are questions about the relationships between risk, regulation, and failure. The credit crisis can be viewed as a type of financial market network failure. The credit crisis underscores the complex and linked nature of contemporary financial markets, as well as the inherent difficulties regulators and industry participants face in managing complex and interconnected risks. The credit crisis also demonstrates that neither industry participants nor regulators fully apprehended underlying financial market risks. In recent years, financial products and financial markets have become increasingly complex and global. Although public commentary and policy discussions in the credit crisis aftermath focused on the implications of financial services firms that are “too big to fail,” existing commentary devotes less attention to the network-like characteristics of financial markets and the implications of complex networks for financial markets. The impact of financial market networks is heightened by the pervasive cultures of trading and risk-taking that now characterize many market segments. The risk-taking associated with financial market trading activities is perhaps best illustrated by cases of individual traders who took on risky trading positions that significantly compromised or, in the case of Baring Brothers, destroyed the firms on whose account they trade

Risky Business: The Credit Crisis and Failure (Part I)

The credit crisis represents a watershed event for global financial markets and has been linked to significant declines in real economy performance on a level of magnitude not experienced since World War II. Recognition of the crisis in 2008 has been followed in 2009 and 2010 by a plethora of competing proposals in response to the credit crisis. The result has been a cacophony of visions, voices, and approaches. The sheer noise that has ensued threatens to drown out the fundamental core questions that should be asked about the credit crisis. Among the most important are questions about the relationships between risk, regulation, and failure. The credit crisis can be viewed as a type of financial market network failure. The credit crisis underscores the complex and linked nature of contemporary financial markets, as well as the inherent difficulties regulators and industry participants face in managing complex and interconnected risks. The credit crisis also demonstrates that neither industry participants nor regulators fully apprehended underlying financial market risks. In recent years, financial products and financial markets have become increasingly complex and global. Although public commentary and policy discussions in the credit crisis aftermath focused on the implications of financial services firms that are “too big to fail,” existing commentary devotes less attention to the network-like characteristics of financial markets and the implications of complex networks for financial markets. The impact of financial market networks is heightened by the pervasive cultures of trading and risk-taking that now characterize many market segments. The risk-taking associated with financial market trading activities is perhaps best illustrated by cases of individual traders who took on risky trading positions that significantly compromised or, in the case of Baring Brothers, destroyed the firms on whose account they trade

Cascading Failures and Fundamental Uncertainty: Divergence in Financial Risk Assessment

By applying common financial risk assessment models to the network economy formalized in Delli Gatti et al. (2006), and by contextualizing both in the broader literature on complexity in economic systems, the question of convergence in economic models is addressed. Critically, a formal state condition is identified which can contribute to the emergence of periods of extreme divergence from expected conditions even in a model characterized by restrictive assumptions regarding agent choice and market structure. The strength of the impact of this state condition, here the topology of a credit network, on the dynamics of the economic system is furthermore shown to be highly dependent upon the structure of the market. The existence of such state conditions has fundamental implications for the evaluation of risk and institutional design in economic system

Reporte Estabilidad Financiera - Primer Semestre de 2020

In the face of the multiple shocks currently experienced by the domestic economy (resulting from the drop in oil prices and the appearance of a global pandemic), the Colombian financial system is in a position of sound solvency and adequate liquidity. At the same time, credit quality has been recovering and the exposure of credit institutions to firms with currency mismatches has declined relative to previous episodes of sudden drops in oil prices. These trends are reflected in the recent fading of red and blue tonalities in the performance and credit risk segments of the risk heatmaps in Graphs A and B.1 Naturally, the sudden, unanticipated change in macroeconomic conditions has caused the appearance of vulnerabilities for short-term financial stability. These vulnerabilities require close and continuous monitoring on the part of economic authorities. The main vulnerability is the response of credit and credit risk to a potential, temporarily extreme macroeconomic situation in the context of: (i) recently increased exposure of some banks to household sector, and (ii) reductions in net interest income that have led to a decline in the profitability of the banking business in the recent past. Furthermore, as a consequence of greater uncertainty and risk aversion, occasional problems may arise in the distribution of liquidity between agents and financial markets. With regards to local markets, spikes have been registered in the volatility of public and private fixed income securities in recent weeks that are consistent with the behavior of the international markets and have had a significant impact on the liquidity of those instruments (red portions in the most recent past of some market risk items on the map in Graph A). In order to adopt a forward-looking approach to those vulnerabilities, this Report presents a stress test that evaluates the resilience of credit institutions in the event of a hypothetical scenario thatseeks to simulate an extreme version of current macroeconomic conditions. The scenario assumes a hypothetical negative growth that is temporarily strong but recovers going into the middle of the coming year and has extreme effects on credit quality. The results suggest that credit institutions have the ability to withstand a significant deterioration in economic conditions in the short term. Even though there could be a strong impact on credit, liquidity, and profitability under the scenario being considered, aggregate capital ratios would probably remain at above their regulatory limits over the horizon of a year. In this context, the recent measures taken by both Banco de la República and the Office of the Financial Superintendent of Colombia that are intended to help preserve the financial stability of the Colombian economy become highly relevant. In compliance with its constitutional objectives and in coordination with the financial system’s security network, Banco de la República will continue to closely monitor the outlook for financial stability at this juncture and will make the decisions that are necessary to ensure the proper functioning of the economy, facilitate the flow of sufficient credit and liquidity resources, and further the smooth functioning of the payment system. Juan José Echavarría Governo

Financial distress prediction using the hybrid associative memory with translation

This paper presents an alternative technique for financial distress prediction systems. The method is based on a type of neural network, which is called hybrid associative memory with translation. While many different neural network architectures have successfully been used to predict credit risk and corporate failure, the power of associative memories for financial decision-making has not been explored in any depth as yet. The performance of the hybrid associative memory with translation is compared to four traditional neural networks, a support vector machine and a logistic regression model in terms of their prediction capabilities. The experimental results over nine real-life data sets show that the associative memory here proposed constitutes an appropriate solution for bankruptcy and credit risk prediction, performing significantly better than the rest of models under class imbalance and data overlapping conditions in terms of the true positive rate and the geometric mean of true positive and true negative rates.This work has partially been supported by the Mexican CONACYT through the Postdoctoral Fellowship Program [232167], the Spanish Ministry of Economy [TIN2013-46522-P], the Generalitat Valenciana [PROMETEOII/2014/062] and the Mexican PRODEP [DSA/103.5/15/7004]. We would like to thank the Reviewers for their valuable comments and suggestions, which have helped to improve the quality of this paper substantially