955 resultados para credit risk


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The paper studies the relationship between four differently rated bank’s financial profile and their standalone credit rating issued by Moody’s. The comparative analysis shows an example that despite their pricing power and geographical coverage, larger banks do not necessarily have better credit ratings. Instead, business model and risk appetite seem to be the defining factors of banks’ vulnerability to shocks, such as the Spanish real estate crisis. The risk-return relationship is also identified in the banks’ fundamentals meaning that while expansionary strategy in riskier asset classes enhances margins, it also potentially distorts the credit risk profile.

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The purpose of this work is to develop a practicable approach for Telecom firms to manage the credit risk exposition to their commercial agents’ network. Particularly it will try to approach the problem of credit concession to clients’ from a corporation perspective and explore the particular scenario of agents that are part of the commercial chain of the corporation and therefore are not end-users. The agents’ network that served as a model for the presented study is composed by companies that, at the same time, are both clients and suppliers of the Telecommunication Company. In that sense the credit exposition analysis must took into consideration all financial fluxes, both inbound and outbound. The current strain on the Financial Sector in Portugal, and other peripheral European economies, combined with the high leverage situation of most companies, generates an environment prone to credit default risk. Due to these circumstances managing credit risk exposure is becoming increasingly a critical function for every company Financial Department. The approach designed in the current study combined two traditional risk monitoring tools: credit risk scoring and credit limitation policies. The objective was to design a new credit monitoring framework that is more flexible, uses both external and internal relationship history to assess risk and takes into consideration commercial objectives inside the agents’ network. Although not explored at length, the blueprint of a Credit Governance model was created for implementing the new credit monitoring framework inside the telecom firm. The Telecom Company that served as a model for the present work decided to implement the new Credit Monitoring framework after this was presented to its Executive Commission.

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This thesis examines the quality of credit ratings issued by the three major credit rating agencies - Moody’s, Standard and Poor’s and Fitch. If credit ratings are informative, then prices of underlying credit instruments such as fixed-income securities and credit default insurance should change to reflect the new credit risk information. Using data on 246 different major fixed income securities issuers and spanning January 2000 to December 2011, we find that credit default swaps (CDS) spreads do not react to changes in credit ratings. Hence credit ratings for all three agencies are not price informative. CDS prices are mostly determined by historical CDS prices while ratings are mostly determined by historical ratings. We find that credit ratings are marginally more sensitive to CDS than CDS are sensitive to ratings.

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This paper investigates the role of credit and liquidity factors in explaining corporate CDS price changes during normal and crisis periods. We find that liquidity risk is more important than firm-specific credit risk regardless of market conditions. Moreover, in the period prior to the recent “Great Recession” credit risk plays no role in explaining CDS price changes. The dominance of liquidity effects casts serious doubts on the relevance of CDS price changes as an indicator of default risk dynamics. Our results show how multiple liquidity factors including firm specific and aggregate liquidity proxies as well as an asymmetric information measure are critical determinants of CDS price variations. In particular, the impact of informed traders on the CDS price increases when markets are characterised by higher uncertainty, which supports concerns of insider trading during the crisis.

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In this paper we investigate the price discovery process in single-name credit spreads obtained from bond, credit default swap (CDS), equity and equity option prices. We analyse short term price discovery by modelling daily changes in credit spreads in the four markets with a vector autoregressive model (VAR). We also look at price discovery in the long run with a vector error correction model (VECM). We find that in the short term the option market clearly leads the other markets in the sub-prime crisis (2007-2009). During the less severe sovereign debt crisis (2009-2012) and the pre-crisis period, options are still important but CDSs become more prominent. In the long run, deviations from the equilibrium relationship with the option market still lead to adjustments in the credit spreads observed or implied from other markets. However, options no longer dominate price discovery in any of the periods considered. Our findings have implications for traders, credit risk managers and financial regulators.

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This contribution offers an explanation of credit derivatives as a group of financial instruments having a common purpose being the managing of credit exposures, and thus credit or default risk. This paper explores the links between their economic and financial manifestations and the legal bases for their widespread application. To ensure an understanding of the purposes served by each of the main types of credit derivatives, a detailed scrutiny of individual instruments is undertaken. Issues relating law and economics to trading in this type of derivative are investigated, then pricing issues and empirical evidence are considered. A summary brings together the range of features bearing upon the effective development of a market in these financial instruments.

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We address credit cycle dependent sovereign credit risk determinants. In our model, the spread determinants' magnitude is conditional on an unobservable endogenous sovereign credit cycle as represented by the underlying state of a Markov regime switching process. Our explanatory variables are motivated in the tradition of structural credit risk models and include changes in asset prices, interest rates, implied market volatility, gold price changes and foreign exchange rates. We examine daily frequency variations of U.S. dollar denominated Eurobond credit spreads of four major Latin American sovereign bond issuers (Brazil, Colombia, Mexico and Venezuela) with liquid bond markets during March 2000 to June 2011. We find that spread determinants are statistically significant and consistent with theory, while their magnitude remarkably varies with the state of the credit cycle. Crisis states are characterized by high spread change uncertainty and high sensitivities with respect to the spread change determinants. We further document that not only changes of local currencies, but also changes of the Euro with respect to the U.S. dollar are significant spread drivers and argue that this is consistent with the sovereigns' ability to pay.

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Este trabalho explora a realização de default soberano em função da estrutura de spreads de CDS (Credit Default Swap). Pode-se dizer que os spreads revelam a probabilidade de default de um país. Aplicamos a metodologia proposta neste trabalho para Argentina, Coreia, Equador, Indonésia, México, Peru, Turquia, Ucrânia, Venezuela e Rússia. Nós mostramos que um modelo de um único fator seguindo um processo lognormal captura a probabilidade de default. Também mostramos que as variáveis macro econômicas inflação, desemprego e crescimento não explicam a variável dependente do estudo (probabilidade de default). Cada país reage de maneira diferente a crise econômica que a leva a não honrar seus compromissos com as dívidas contraídas.

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Lenders can tap into multiple sources of private information to assess consumer credit risk but little is known about the informational synergies between these sources. Using unique panel data on checking accounts and credit card accounts from the same customers during 2007-2014, we find that activity measures from both account types contain information beyond credit scores and other controls. Checking accounts display warning indications earlier and more accurately than credit card accounts. We also investigate the consistency of information, the reasons for defaults, and selection effects. The evidence highlights sizeable informational synergies that lenders can use to manage credit relationships.

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This PhD Thesis is composed of three chapters, each discussing a specific type of risk that banks face. The first chapter talks about Systemic Risk and how banks get exposed to it through the Interbank Funding Market. Exposures in the said market have Systemic Risk implications because the market creates linkages, where the failure of one party can affect the others in the market. By showing that CDS Spreads, as bank risk indicators, are positively related to their Net Interbank Funding Market Exposures, this chapter establishes the above Systemic Risk Implications of Interbank Funding. Meanwhile, the second chapter discusses how banks may handle Illiquidity Risk, defined as the possibility of having sudden funding needs. Illiquidity Risk is embodied in this chapter through Loan Commitments as they oblige banks to lend to its clients, up to a certain amount of funds at any time. This chapter points out that using Securitization as funding facility, could allow the banks to manage this Illiquidity Risk. To make this case, this chapter demonstrates empirically that banks having an increase in Loan Commitments, may experience an increase in risk profile but such can be offset by an accompanying increase in Securitization Activity. Lastly, the third chapter focuses on how banks manage Credit Risk also through Securitization. Securitization has a Credit Risk management property by allowing the offloading of risk. This chapter investigates how banks use such property by looking at the effect of securitization on the banks’ loan portfolios and overall risk and returns. The findings are that securitization is positively related to loan portfolio size and the portfolio share of risky loans, which translates to higher risk and returns. Thus, this chapter points out that Credit Risk management through Securitization may be have been done towards higher risk taking for high returns.

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(Matsukawa and Habeck, 2007) analyse the main instruments for risk mitigation in infrastructure financing with Multilateral Financial Institutions (MFIs). Their review coincided with the global financial crisis of 2007-08, and is highly relevant in current times considering the sovereign debt crisis, the lack of available capital and the increases in bank regulation in Western economies. The current macroeconomic environment has seen a slowdown in the level of finance for infrastructure projects, as they pose a higher credit risk given their requirements for long term investments. The rationale for this work is to look for innovative solutions that are focused on the credit risk mitigation of infrastructure and energy projects whilst optimizing the economic capital allocation for commercial banks. This objective is achieved through risk-sharing with MFIs and looking for capital relief in project finance transactions. This research finds out the answer to the main question: "What is the impact of risk-sharing with MFIs on project finance transactions to increase their efficiency and viability?", and is developed from the perspective of a commercial bank assessing the economic capital used and analysing the relevant variables for it: Probability of Default, Loss Given Default and Recovery Rates, (Altman, 2010). An overview of project finance for the infrastructure and energy sectors in terms of the volume of transactions worldwide is outlined, along with a summary of risk-sharing financing with MFIs. A review of the current regulatory framework beneath risk-sharing in structured finance with MFIs is also analysed. From here, the impact of risk-sharing and the diversification effect in infrastructure and energy projects is assessed, from the perspective of economic capital allocation for a commercial bank. CreditMetrics (J. P. Morgan, 1997) is applied over an existing well diversified portfolio of project finance infrastructure and energy investments, working with the main risk capital measures: economic capital, RAROC, and EVA. The conclusions of this research show that economic capital allocation on a portfolio of project finance along with risk-sharing with MFIs have a huge impact on capital relief whilst increasing performance profitability for commercial banks. There is an outstanding diversification effect due to the portfolio, which is combined with risk mitigation and an improvement in recovery rates through Partial Credit Guarantees issued by MFIs. A stress test scenario analysis is applied to the current assumptions and credit risk model, considering a downgrade in the rating for the commercial bank (lender) and an increase of default in emerging countries, presenting a direct impact on economic capital, through an increase in expected loss and a decrease in performance profitability. Getting capital relief through risk-sharing makes it more viable for commercial banks to finance infrastructure and energy projects, with the beneficial effect of a direct impact of these investments on GDP growth and employment. The main contribution of this work is to promote a strategic economic capital allocation in infrastructure and energy financing through innovative risk-sharing with MFIs and economic pricing to create economic value added for banks, and to allow the financing of more infrastructure and energy projects. This work suggests several topics for further research in relation to issues analysed. (Matsukawa and Habeck, 2007) analizan los principales instrumentos de mitigación de riesgos en las Instituciones Financieras Multilaterales (IFMs) para la financiación de infraestructuras. Su presentación coincidió con el inicio de la crisis financiera en Agosto de 2007, y sus consecuencias persisten en la actualidad, destacando la deuda soberana en economías desarrolladas y los problemas capitalización de los bancos. Este entorno macroeconómico ha ralentizado la financiación de proyectos de infraestructuras. El actual trabajo de investigación tiene su motivación en la búsqueda de soluciones para la financiación de proyectos de infraestructuras y de energía, mitigando los riesgos inherentes, con el objeto de reducir el consumo de capital económico en los bancos financiadores. Este objetivo se alcanza compartiendo el riesgo de la financiación con IFMs, a través de estructuras de risk-sharing. La investigación responde la pregunta: "Cuál es el impacto de risk-sharing con IFMs, en la financiación de proyectos para aumentar su eficiencia y viabilidad?". El trabajo se desarrolla desde el enfoque de un banco comercial, estimando el consumo de capital económico en la financiación de proyectos y analizando las principales variables del riesgo de crédito, Probability of Default, Loss Given Default and Recovery Rates, (Altman, 2010). La investigación presenta las cifras globales de Project Finance en los sectores de infraestructuras y de energía, y analiza el marco regulatorio internacional en relación al consumo de capital económico en la financiación de proyectos en los que participan IFMs. A continuación, el trabajo modeliza una cartera real, bien diversificada, de Project Finance de infraestructuras y de energía, aplicando la metodología CreditMet- rics (J. P. Morgan, 1997). Su objeto es estimar el consumo de capital económico y la rentabilidad de la cartera de proyectos a través del RAROC y EVA. La modelización permite estimar el efecto diversificación y la liberación de capital económico consecuencia del risk-sharing. Los resultados muestran el enorme impacto del efecto diversificación de la cartera, así como de las garantías parciales de las IFMs que mitigan riesgos, mejoran el recovery rate de los proyectos y reducen el consumo de capital económico para el banco comercial, mientras aumentan la rentabilidad, RAROC, y crean valor económico, EVA. En escenarios económicos de inestabilidad, empeoramiento del rating de los bancos, aumentos de default en los proyectos y de correlación en las carteras, hay un impacto directo en el capital económico y en la pérdida de rentabilidad. La liberación de capital económico, como se plantea en la presente investigación, permitirá financiar más proyectos de infraestructuras y de energía, lo que repercutirá en un mayor crecimiento económico y creación de empleo. La principal contribución de este trabajo es promover la gestión activa del capital económico en la financiación de infraestructuras y de proyectos energéticos, a través de estructuras innovadoras de risk-sharing con IFMs y de creación de valor económico en los bancos comerciales, lo que mejoraría su eficiencia y capitalización. La aportación metodológica del trabajo se convierte por su originalidad en una contribución, que sugiere y facilita nuevas líneas de investigación académica en las principales variables del riesgo de crédito que afectan al capital económico en la financiación de proyectos.

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We uncover high persistence in credit spread series that can obscure the relationship between the theoretical determinants of credit risk and observed credit spreads. We use a Markovswitching model, which also captures the stability (low frequency changes) of credit ratings, to show why credit spreads may continue to respond to past levels of credit risk, even though the state of the economy has changed. A bivariate model of credit spreads and either macroeconomic activity or equity market volatility detects large and significant correlations that are consistent with theory but have not been observed in previous studies. © 2010 Nova Science Publishers, Inc. All rights reserved.

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Nowadays financial institutions due to regulation and internal motivations care more intensively on their risks. Besides previously dominating market and credit risk new trend is to handle operational risk systematically. Operational risk is the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. First we show the basic features of operational risk and its modelling and regulatory approaches, and after we will analyse operational risk in an own developed simulation model framework. Our approach is based on the analysis of latent risk process instead of manifest risk process, which widely popular in risk literature. In our model the latent risk process is a stochastic risk process, so called Ornstein- Uhlenbeck process, which is a mean reversion process. In the model framework we define catastrophe as breach of a critical barrier by the process. We analyse the distributions of catastrophe frequency, severity and first time to hit, not only for single process, but for dual process as well. Based on our first results we could not falsify the Poisson feature of frequency, and long tail feature of severity. Distribution of “first time to hit” requires more sophisticated analysis. At the end of paper we examine advantages of simulation based forecasting, and finally we concluding with the possible, further research directions to be done in the future.

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In - Protecting Your Assets: A Well-Defined Credit Policy Is The Key – an essay by Steven V. Moll, Associate Professor, The School of Hospitality Management at Florida International University, Professor Moll observes at the outset: “Bad debts as a percentage of credit sales have climbed to record levels in the industry. The author offers suggestions on protecting assets and working with the law to better manage the business.” “Because of the nature of the hospitality industry and its traditional liberal credit policies, especially in hotels, bad debts as a percentage of credit sales have climbed to record levels,” our author says. “In 1977, hotels showing a net income maintained an average accounts receivable ratio to total sales of 3.4 percent. In 1983, the accounts receivable ratio to total sales increased to 4.1 percent in hotels showing a net income and 4.4 percent in hotels showing a net loss,” he further cites. As the professor implies, there are ways to mitigate the losses from bad credit or difficult to collect credit sales. In this article Professor Moll offers suggestions on how to do that. Moll would suggest that hotels and food & beverage operations initially tighten their credit extension policies, and on the following side, be more aggressive in their collection-of-debt pursuits. There is balance to consider here and bad credit in and of itself as a negative element is not the only reflection the profit/loss mirror would offer. “Credit managers must know what terms to offer in order to compete and afford the highest profit margin allowable,” Moll says. “They must know the risk involved with each guest account and be extremely alert to the rights and wrongs of good credit management,” he advocates. A sound profit policy can be the result of some marginal and additional credit risk on the part of the operation manager. “Reality has shown that high profits, not small credit losses, are the real indicator of good credit management,” the author reveals. “A low bad debt history may indicate that an establishment has an overly conservative credit management policy and is sacrificing potential sales and profits by turning away marginal accounts,” Moll would have you believe, and the science suggests there is no reason not to. Professor Moll does provide a fairly comprehensive list to illustrate when a manager would want to adopt a conservative credit policy. In the final analysis the design is to implement a policy which weighs an acceptable amount of credit risk against a potential profit ratio. In closing, Professor Moll does offer some collection strategies for loose credit accounts, with reference to computer and attorney participation, and brings cash and cash discounts into the discussion as well. Additionally, there is some very useful information about what debt collectors – can’t – do!

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As a response to the inefficient practices and possibly misleading inferences resulting from the unit-by-unit application mostly found in the literature, the current paper develops a block bootstrap based panel predictability test procedure that accommodates multiple predictors. As an empirical illustration we consider emerging market sovereign risk where data are usually available across multiple countries, and local and global predictors. The results, which are in agreement with the existing literature on the determinants of sovereign risk, suggest that the global predictors are best and that the predictive ability of the local predictors is limited, at best.