Showing papers on "Credit risk published in 1996"

Determinants and Impact of Sovereign Credit Ratings

Abstract: n recent years, the demand for sovereign credit rat-ings—the risk assessments assigned by the creditrating agencies to the obligations of central govern-ments—has increased dramatically. More govern-ments with greater default risk and more companiesdomiciled in riskier host countries are borrowing in inter-national bond markets. Although foreign government offi-cials generally cooperate with the agencies, ratingassignments that are lower than anticipated often promptissuers to question the consistency and rationale of sover-eign ratings. How clear are the criteria underlying sover-eign ratings? Moreover, how much of an impact do ratingshave on borrowing costs for sovereigns?To explore these questions, we present the firstsystematic analysis of the determinants and impact of thesovereign credit ratings assigned by the two leading U.S.agencies, Moody’s Investors Service and Standard andPoor’s.

Estimating the Price of Default Risk

Abstract: The risk of default affects virtually every financial contract. Therefore the pricing of default risk has received much attention; both from traders, who have a strong interest in pricing transactions accurately, and from financial economists, who have much to learn from the way such risks are priced in markets. The standard theoretical paradigm for modeling credit risks is the contingent claims approach pioneered by Black and Scholes. Much of the literature follows Merton (1974) by explicitly linking the risk of a firm’s default to the variability in the firm’s asset value. Although this line of research has proven very useful in addressing the qualitatively important aspects of

System and method to performing on-line credit reviews and approvals

Abstract: A user-friendly on-line computerized system operates in real-time thus streamlining the processing of applications for products and services offered by a financial institution The system automates many steps in the credit and liability review and approval process, performs background credit worthiness evaluations based upon a applicant's credit score, financial information and new or existing relationship with the financial institution, recommends to those applicants who exceed the initial criteria for credit consideration specific credit products with predetermined credit qualified offer amounts, and ensures the required operating (credit/liability) policies are appropriately completed The system immediately analyzes an applicant's credit bureau history and automated credit scoring, and provides these results to the LBR The system also takes into account information relating to the applicant's new or existing relationship with the financial institution, if any, into the credit decision request This enables the system to provide applicants with an up-front conditional approval (based on systematic evaluation of credit bureau history, credit score, debt burden, and applicant's new or existing relationship deposits), subject to required verifications

Financial Institutions Management: A Risk Management Approach

Abstract: Part I Introduction Ch. 1 Why Are Financial Institutions Special? Appendix 1A The Financial Crisis: The Failure of Financial Services Institution Specialness (online) Appendix 1B Monetary Policy Tools (online) Ch. 2 Financial Services: Depository Institutions Appendix 2A Financial Statement Analysis Using a Return on Equity (ROE) Framework (online) Appendix 2B Commercial Banks' Financial Statements and Analysis (online) Appendix 2C Depository Institutions and Their Regulators (online) Appendix 2D Technology in Commercial Banking (online) Ch. 3 Financial Services: Finance Companies Ch. 4 Financial Services: Securities Brokerage and Investment Banking Ch. 5 Financial Services: Mutual Funds and Hedge Funds Ch. 6 Financial Services: Insurance Ch. 7 Risks of Financial Institutions Part II Measuring Risk Ch. 8 Interest Rate Risk I Appendix 8A The Maturity Model (online) Appendix 8B Term Structure of Interest Rates Ch. 9 Interest Rate Risk II Appendix 9A The Basics of Bond Valuation (online) Appendix 9B Incorporating Convexity into the Duration Model Ch. 10 Credit Risk: Individual Loan Risk Appendix 10A Credit Analysis (online) Appendix 10B Black-Scholes Option Pricing Model (online) Ch. 11 Credit Risk: Loan Portfolio and Concentration Risk Appendix 11A CreditMetrics Appendix 11B CreditRisk+ Ch. 12 Liquidity Risk Appendix 12A Sources and Uses of Funds Statement, Bank of America, March 2012 (online) Ch. 13 Foreign Exchange Risk Ch. 14 Sovereign Risk Appendix 14A Mechanisms for Dealing with Sovereign Risk Exposure Ch. 15 Market Risk Ch. 16 Off-Balance-Sheet Risk Appendix 16A A Letter of Credit Transaction (online) Ch. 17 Technology and Other Operational Risks Part III Managing Risk Ch. 18 Liability and Liquidity Management Appendix 18A Federal Reserve Requirement Accounting (online) Appendix 18B Bankers Acceptances and Commercial Paper as Sources of Financing (online) Ch. 19 Deposit Insurance and Other Liability Guarantees Appendix 19A Calculation of Deposit Insurance Premiums Appendix 19B FDIC Press Releases of Bank Failures (online) Appendix 19C Deposit Insurance Coverage for Commercial Banks in Various Countries (online) Ch. 20 Capital Adequacy Appendix 20A Internal Ratings-Based Approach to Measuring Credit Risk-Adjusted Assets Appendix 20B Methodology Used to Determine G-SIBs Capital Surcharge (online) Ch. 21 Product and Geographic Expansion Appendix 21A EU and G-10 Countries: Regulatory Treatment of the Mixing of Banking, Securities, and Insurance Activities and the Mixing of Banking and Commerce (online) Ch. 22 Futures and Forwards Appendix 22A Microhedging with Futures (online) Ch. 23 Options, Caps, Floors, and Collars Appendix 23A Black-Scholes Option Pricing Model (online) Appendix 23B Microhedging with Options (online) Ch. 24 Swaps Appendix 24A Setting Rates on an Interest Rate Swap Ch. 25 Loan Sales Ch. 26 Securitization Appendix 26A Fannie Mae and Freddie Mac Balance Sheets (online)

Special Repo Rates

Abstract: This article provides the causes and symptoms of special repo rates in a competitive market for repurchase agreements. A repo rate is, in effect, an interest rate on loans collateralized by a specific instrument. A "special" is a repo rate significantly below prevailing market riskless interest rates. This article shows that specials can occur when those owning the collateral are inhibited, whether from legal or institutional requirements or from frictional costs, from supplying collateral into repurchase agreements. Specialness increases the equilibrium price for the underlying instrument by the present value of savings in borrowing costs associated with the repo specials. THIS ARTICLE CHARACTERIZES COMPETITIVE repurchase, or "repo," markets, and the equilibrium relationship between repo rates and the underlying cash market prices. Repurchase markets are often called "financing" markets since they are effectively vehicles for collateralized borrowing that are often used to finance the purchase of the underlying collateral. This article provides causes and effects of "specials," meaning specific repo rates significantly below prevailing market interest rates for loans of similar maturity and credit risk. The example of United States Treasury instruments is emphasized because of the extensive use of the Treasury repo market as a means of hedging against, or speculating on, changes in U.S. interest rates, and because of the high incidence of specials in Treasury repo rates. Numerous specific instru

Determinants and Impact of Sovereign Credit Ratings

Abstract: The authors conduct the first systematic analysis of the determinants and impact of the sovereign credit ratings assigned by the two leading U.S. agencies, Moody's Investor Services and Standard and Poor's. Of the large number of criteria used by the two agencies, six factors appear to play an important role in determining a country's credit rating: per capita income, GDP growth, inflation, external debt, level of economic development, and default history. In addition, the authors find that sovereign ratings influence market yields - particularly those on non-investment-grade issues - independently of any correlation with publicly available information.

A k-nearest-neighbour classifier for assessing consumer credit risk

Abstract: SUMMARY The last 30 years have seen the development of credit scoring techniques for assessing the creditworthiness of consumer loan applicants. Traditional credit scoring methodology has involved the use of techniques such as discriminant analysis, linear or logistic regression, linear programming and decision trees. In this paper we look at the application of the k-nearest-neighbour (k-NN) method, a standard technique in pattern recognition and nonparametric statistics, to the credit scoring problem. We propose an adjusted version of the Euclidean distance metric which attempts to incorporate knowledge of class separation contained in the data. Our k-NN methodology is applied to a real data set and we discuss the selection of optimal values of the parameters k and D included in the method. To assess the potential of the method we make comparisons with linear and logistic regression and decision trees and graphs. We end by discussing a practical implementation of the proposed k-NN classifier.

Pricing Credit-Sensitive Debt When Interest Rates, Credit Ratings and Credit Spreads are Stochastic

Abstract: This paper develops a model for the pricing of credit-sensitive debt contracts. Over the past two decades, the debt markets have seen a proliferation of contracts designed to reapportion interest rate and credit risks between issuer and investors. Contracts including credit-sensitive notes (CSNs), spread adjusted notes (SPANs), and floating rate notes (FRNs) adjust investors' exposures to three risks: interest rate risk, changes in credit risk caused by changes in the credit rating of the issuer of the debt, and changes in credit risk caused by changes in spreads on the debt, even when ratings have not changed. In the paper, we develop a pricing model incorporating all three risks, with special emphasis on credit risks. The model incorporates a decomposition of credit spreads into two stochastic elements: the default process and the recovery process in the event of default. The model is easily implementable as it uses observable inputs. By using a discrete time formulation the model is numerically easy to employ, and also permits the pricing of debt with embedded options of American type. It also allows for pricing contracts between parties with varying credit ratings such as swaps where each counterparty may have different credit quality. These features impart a degree of generality and practicality to the model which should make it attractive to academics and practitioners alike.

Expected Returns and Volatility in 135 Countries

Abstract: We analyze expected returns and volatility in 135 different markets. We argue that country credit risk is a proxy for the ex-ante risk exposure of, particularly, segmented developing countries. We fit a time-series cross-sectional regression using data on the 47 countries which have equity markets. These regressions predict both expected returns and volatility using credit risk as a single explanatory variable. We then use the credit rating data on the other 88 countries to project hurdle rates and volatility into the future. Finally, we calculate for each country, the expected time in years, given the forecasted country risk premium and volatility, for an investor to break even and double the initial investment - with 90% probability. This is the final working paper version of our 1996 Journal of Portfolio Management paper.

Recursive valuation of defaultable securities and the timing of resolution of uncertainty

Abstract: We derive the implications of default risk for valuation of securities in an abstract setting in which the fractional default recovery rate and the hazard rate for default may depend on the market value of the instrument itself, or on the market values of other instruments issued by the same entity (which are determined simultaneously). A key technique is the use of backward recursive stochastic integral equations. We characterize the dependence of the market value on the manner of resolution of uncertainty, and in particular give conditions for monotonicity of value with respect to the information filtration.

Credit Risk, Credit Scoring, and the Performance of Home Mortgages

Abstract: This article examines the ways institutions involved in mortgage lending assess credit risk and how credit risk relates to loan performance. An increasingly prominent tool used to facilitate the assessment of credit risk in mortgage lending is credit scoring based on credit history and other pertinent data, and the article presents new information about the distribution of credit scores across population groups and how credit scores relate to the performance of loans. In addition, this article takes a special look at the performance of loans made through nontraditional underwriting practices and "affordable" home lending programs.

Determinants and impacts of sovereign credit ratings

Abstract: In this article, we present the first systematic analysis of the sovereign credit ratings of the two leading agencies, Moody's and Standard & Poor's (S&P). We find that the ordering of risks they imply is broadly consistent with macroeconomic fundamentals. While the agencies cite a large number of criteria in their assignment of sovereign ratings, a regression using only eight factors explains more than 90 percent of the cross-sectional variation in the ratings. In particular, a country's rating appears largely determined by its per capita income, external debt burden, inflation experience, default history and level of economic development. We do not, however, find any systematic relationship between ratings and either fiscal or current deficits, perhaps because of the endogeneity of fiscal policy and international capital flows. Sovereign ratings are also closely related to market-determined credit spreads, effectively summarizing and supplementing the information content of macroeconomic indicators in the pricing of sovereign risk. Cross-sectional results suggest that the rating agencies' opinions have independent effects on market spreads. Event study analysis broadly confirms this qualitative conclusion, for the reactions of bond yields to the announcements of changes in the agencies' sovereign risk opinions are statistically significant with respect to both their sign and magnitude.

Scenario Simulation: Theory and methodology

Abstract: This paper presents a new simulation methodology for quantitative risk analysis of large multi-currency portfolios The model discretizes the multivariate distribution of market variables into a limited number of scenarios This results in a high degree of computational efficiency when there are many sources of risk and numerical accuracy dictates a large Monte Carlo sample Both market and credit risk are incorporated The model has broad applications in financial risk management, including value at risk Numerical examples are provided to illustrate some of its practical applications

Sovereign risk assessment and agency credit ratings

Abstract: Sovereign ratings are gaining importance as more governments with greater default risk borrow in international bond markets. However, while the ratings have proved useful to governments seeking market access, the difficulty of assessing sovereign risk has led to agency disagreements and public controversy over specific rating assignments. Recognising this difficulty, the financial markets have shown some scepticism toward sovereign ratings when pricing issues.

Valuing and accounting for loan guarantees

Abstract: To achieve certain policy objectives, governments frequently provide private borrowers with loan guarantees that cover some or all of the risk that the borrower will be unable to repay the loan. Such guarantees are extremely valuable, and their value increases with the riskiness of the underlying asset or credit, the size of the investment, and the duration of the loan. The flip side of a guarantee's value to a lender is its cost to the government. Such a cost is not explicit but is real nevertheless. When providing guarantees, governments therefore must establish accounting, valuation, and risk-sharing mechanisms. This article describes methods of valuing guarantees; reports estimates of the value of guarantees in different settings; and summarizes new methods of accounting designed to anticipate losses, create reserves, and channel funds through transparent accounts to ensure that the costs of guarantees are evident to government decisionmakers.

On measuring credit risks of derivative instruments

Abstract: This paper critically reviews current practices for measuring credit risks of derivative instruments. It argues that there are two major problems with the standard measurement approach. First, it uses models of the stoachstic behavior of finanacial variables while ignoring both their inherent oversimplification and the uncertainty in their parameters. Second, it ignores the correlations among exposures in derivative intruments and the probabilities of countrypartly default. This paper deomonstrates that these practices can produce large errors in the estimation of distribution of both future credit exposures and future credit losses.

Credit Derivatives: New Financial Instruments for Controlling Credit Risk

Abstract: One of the risks of making a bank loan or investing in a debt security is credit risk, the risk of borrower default In response to this potential problem, new financial instruments called credit derivatives have been developed in the past few years Credit derivatives can help banks, financial companies, and investors manage the credit risk of their investments by insuring against adverse movements in the credit quality of the borrower If a borrower defaults, the investor will suffer losses on the investment, but the losses can be offset by gains from the credit derivative Thus, if used properly, credit derivatives can reduce an investor's overall credit risk Estimates from industry sources suggest the credit derivatives market has grown from virtually nothing two years ago to about $20 billion of transactions in 1995 This growth has been driven by the ability of credit derivatives to provide valuable new methods for managing credit risk As with other customized derivative products, however, credit derivatives expose their users to risks and regulatory uncertainty Controlling these risks is likely to be an important factor in the future development of the credit derivatives market This article provides information on the rationale and use of credit derivatives The first section of the article describes how to measure credit risk, whom it affects, and the traditional strategies used to manage it The second section shows how credit derivatives can help manage credit risk The third section examines the risks and regulatory issues associated with credit derivatives CREDIT RISK Credit risk is important to banks, bond issuers, and bond investors If a firm defaults, neither banks nor investors will receive their promised payments While there are a variety of methods for managing credit risk, these methods are typically insufficient to reduce credit risk to desired levels This section defines credit risk, describes how it can be measured, and shows how it affects bond issuers, bond investors, and banks The section also describes the techniques most commonly used to manage credit risk, such as loan underwriting standards, diversification, and asset securitization What is credit risk? Credit risk is the probability that a borrower will default on a commitment to repay debt or bank loans Default occurs when the borrower cannot fulfill key financial obligations, such as making interest payments to bondholders or repaying bank loans In the event of default, lenders-bondholders or banks-suffer a loss because they will not receive all the payments promised to theml Credit risk is influenced by both business cycles and firm-specific events Credit risk typically declines during economic expansions because strong earnings keep overall default rates low Credit risk increases during economic contractions because earnings deteriorate, making it more difficult to repay loans or make bond payments Firm-specific credit risk is unrelated to business cycles This risk arises from events specific to a firm's business activities or its industry, events such as product liability lawsuits For example, when the health hazards of asbestos became known, liability lawsuits forced JohnsManville, a leading asbestos producer, into bankruptcy and to default on its bonds A broad measure of a firm's credit risk is its credit rating This measure is useful for categorizing companies according to their credit risk Rating firms, such as Moody's Investors Services, assign a credit rating to a company based on an analysis of the company's financial statements Credit ratings range from Aaa for firms of the highest credit quality, to Ccc for firms likely to default2 A more quantitative measure of credit risk is the credit risk premium The credit risk premium is the difference between the interest rate a firm pays when it borrows and the interest rate on a default-free security, such as a U …

Treasury Yields and Corporate Bond Yield Spreads : An Empirical Analysis

Abstract: This paper empirically examines the relation between the Treasury term structure and spreads of investment grade corporate bond yields over Treasuries. I find that noncallable bond yield spreads fall when the level of the Treasury term structure rises. The extent of this decline depends on the initial credit quality of the bond; the decline is small for Aaa-rated bonds and large for Baa-rated bonds. The role of the business cycle in generating this pattern is explored, as is the link between yield spreads and default risk. I also argue that yield spreads based on commonly-used bond yield indexes are contaminated in two important ways. The first is that they are "refreshed" indexes, which hold credit ratings constant over time; the second is that they usually are constructed with both callable and noncallable bonds. The impact of both of these problems is examined.

Default risk and derivative products

Abstract: The modelling of default risk in debt securities involves making assumptions about the stochastic process driv- ing default, the process generating the write-down in default, and risk-free interest rates. Three generic approaches have been used. The first relies on modelling the value of the assets on which the debt is written. The second involves modelling default as an arrival process. The third involves directly modelling the interest rate spreads to which default gives rise. Each of these approaches may be applied to the impact of default risk on derivative products such as swaps and options. One application is to the valuation of derivative products that may default. The other is to the new class of ‘credit derivatives’ that represent derivative products written on credit risk.

Determinants and Impact of Sovereign Credit Ratings

Abstract: n recent years, the demand for sovereign credit rat-ings—the risk assessments assigned by the creditrating agencies to the obligations of central govern-ments—has increased dramatically. More govern-ments with greater default risk and more companiesdomiciled in riskier host countries are borrowing in inter-national bond markets. Although foreign government offi-cials generally cooperate with the agencies, ratingassignments that are lower than anticipated often promptissuers to question the consistency and rationale of sover-eign ratings. How clear are the criteria underlying sover-eign ratings? Moreover, how much of an impact do ratingshave on borrowing costs for sovereigns?To explore these questions, we present the firstsystematic analysis of the determinants and impact of thesovereign credit ratings assigned by the two leading U.S.agencies, Moody’s Investors Service and Standard andPoor’s.

A Comprehensive Model for Managing Credit Risk on Home Mortgage Portfolios

Abstract: Managing credit risk in financial institutions requires the ability to forecast aggregate losses on existing loans, predict the length of time that loans will be on the books before prepayment or default, analyze the expected performance of particular segments in the existing portfolio, and project payment patterns of new loans. Described in this paper are tools created for these functions in a large California financial institution. A forecasting model with Markovian structure and nonstationary transition probabilities is used to model the life of a mortgage. Logistic and regression models are used to estimate severity of losses. These models are integrated into a system that allows analysts and managers to depict the expected performance of individual loans and portfolio segments under different economic scenarios. With this information, analysts and managers can establish appropriate loss reserves, suggest pricing differentials to compensate for risk, and make strategic lending decisions.

Risk, regulation, and S & L diversification into nontraditional assets

Abstract: Risk exposure is a central issue in the debate over allowing savings and loan associations (S&Ls) to expand into nontraditional activities. This paper examines the relationship between risk and portfolio composition of three distinct groups of S&L lenders based on their investment strategies: real estate specialized (RES) S&L lenders with high holdings of adjustable-rate mortgages (ARMs), RES S&L lenders with low ARMs, and not real estate specialized (NRES) S & L lenders. The major findings of this paper suggest that diversification] into nontraditional assets leads to lower risk and higher average returns for RES firms with low ARMs, but for NRES firms it leads to higher risk and (in some cases) lower average returns. This latter group of institutions appears to be using nontraditional assets as a means to increase their risk exposure and not necessarily their average stock returns. In addition, we find that risk increases for RES S&Ls with high ARMs as additional adjustable-rate mortgages are added to their portfolios. This is not the case for the low ARMs group and may indicate that at some level the increase in credit risk dominates the decrease in interest rate risk associated with additional ARMs, relative to fixed-rate mortgages. These results strongly suggest that while additional diversification provides risk reduction opportunities for some S&Ls, it also provides opportunities for other S&Ls to increase their risk exposure.

Distribution of Credit Risk Among Providers of Mortgages to Lower-Income and Minority Homebuyers

Abstract: Which institutions bear the credit risk for mortgage lending to lower-income and minority borrowers and in lower-income and predominantly minority neighborhoods? In seeking to answer those questions, the authors went beyond looking at mortgage credit risk in terms of numbers or amounts of loans and developed measures based on factors that affect the riskiness of loans, including loan-to-value ratios and associated default and loss severity rates. In 1995, a nonprofit government mortgage insurer, the Federal Housing Administration, was the major bearer of credit risk for mortgage lending to these groups. The amount of credit risk borne by the profit-seeking originators, insurers, and purchasers that finance conventional mortgages was small in comparison, and the risk was widely distributed among different types of institutions. (This abstract was borrowed from another version of this item.)

A Credit Crunch? a Case Study of Finland in the Aftermath of the Banking Crisis

Abstract: This paper estimates a disequilibrium model of credit supply and demand to evaluate whether there was a credit crunch in Finland following the banking crisis of 1991-92. Empirical analysis suggests that the marked reduction in bank lending was mainly in reaction to a cyclical decline in credit demand, likely exacerbated by the high level of indebtedness of the borrowers. It also appears that banks became less willing to supply credit during periods associated with a deterioration in asset quality, and reduced profits due to declining regulatory protection from competition, and a need to increase capital adequacy levels.

The value of recourse and cross-default clauses in commercial mortgage contracting

Abstract: The traditional commercial mortgage contract is written without recourse to any other borrower assets except the subject property. For credit enhancement purposes, many lenders/ investors are today seeking access to additional collateral through recourse or cross-default clauses. This paper considers the contracting value of such clauses. To measure these values and assess other related risk statistics, we apply a contingent-claims approach in which borrowers rationally default when the value of the mortgage meets or exceeds the value of the collateral, where collateral value includes additional assets provided through the mortgage contract. In the case of recourse to an unencumbered asset, default risk is reduced in part simply because additional collateral is available. In addition, when the subject property and additional collateral are less than perfectly correlated, diversification benefits are apparent. In the case of the cross-default clause — which means that default on one loan constitutes default on all loans covered by the clause — risk management benefits are also found to be substantial. For example, default risk resulting from a two-asset cross-default clause arrangement can be reduced by over 50 percent of non-recourse default risk when asset values are uncorrelated.