An analysis of default risk in the Home Equity Conversion Mortgage (HECM) program

While reverse mortgages are intended as a tool to enable financial security for older homeowners, in 2014, nearly 12 percent of reverse mortgage borrowers in the federally insured Home Equity Conversion Mortgage (HECM) program were in default on their property taxes or homeowners insurance. Unlike the traditional mortgage market, there were no risk-based underwriting guidelines for HECMs through 2014. In response to the relatively high default rate, a variety of policy responses were implemented, including establishing underwriting guidelines. However, there is a lack of data and analysis to inform such criteria. Our analysis follows 30,000 seniors counseled for reverse mortgages between 2006 and 2011. The data includes comprehensive financial and credit report attributes, not typically available in analyses of reverse mortgage borrowers. Using a bivariate probit model that accounts for selection, we estimate the likelihood of tax and insurance default. Financial characteristics that increase default risk include the percentage of funds withdrawn in the first month of the loan, a lower credit score, higher property tax to income ratio, low or no unused revolving credit, and a history of being past due on mortgage payments or having a tax lien on the property. Our estimate of the elasticity of default with respect to credit scores is similar to that for closed-end home equity loans, but higher than that for HELOCs. We simulate the effects of alternative underwriting criteria and policy changes on the probability of take-up and default. Reductions in the default rate with a minimal effect on participation can be achieved by requiring that participants with low credit scores set aside some of their HECM funds for future property tax and insurance payments, a form of escrowing.     

Unemployment risk, house price risk and the transition into home ownership in the United Kingdom

Using household panel data, this paper examines the impact of income uncertainty, in the form of unemployment risk, on home ownership in the United Kingdom. The existing literature based on cross-sectional studies finds a negative relationship between income uncertainty and home ownership. This paper utilises data on transitions into home ownership and exogenous variation in unemployment risk, avoiding the endogeneity of employment to home ownership status. It also conditions the empirical estimates on a measure of house price volatility utilising a local-level house price index to control house price risk, which might also discourage home ownership. Results show a strong role for unemployment risk in lowering the likelihood of house purchase, but no statistically significant role for house price risk.     

Determinants of bank interest margins in Russia: Does bank ownership matter?

This paper analyzes interest margin determinants in the Russian banking sector with a particular emphasis on the bank ownership structure. Using unique bank-level data covering Russia's entire banking sector for the 1999–2007 period, we find that the impact of a number of commonly used determinants such as market structure, credit risk, liquidity risk and size of operations differs across state-controlled, domestic-private and foreign-owned banks. At the same time, the influence of operational costs and risk aversion is homogeneous across ownership groups. The results overall suggest that the form of bank ownership needs to be considered when analyzing interest margin determinants.     

Slowdown of credit flows in Jordan in the wake of the global financial crisis: Supply or demand driven?

This paper estimates a disequilibrium model of credit supply and demand to evaluate the relative role of these factors in the slowdown of credit flows in the Jordanian economy in the wake of the global financial crisis. The empirical analysis suggests that the credit stagnation is mainly driven by the restricted credit supply amid tighter monetary policy conditions in Jordan relative to the United States, as evidenced by the widened interest differential between the Central Bank of Jordan (CBJ) re-discount and the U.S. Federal Reserve funds rates. Although it appears that demand side factors related to the slowdown of economic activity have also had an impact, their role has been relatively modest. The estimation results imply that economic policies targeted towards stimulating the supply of credit are likely to be a more effective tool for expanding credit flows relative to demand stimulating policies.     

Transition matrix models of consumer credit ratings

Although the corporate credit risk literature includes many studies modelling the change in the credit risk of corporate bonds over time, there has been far less analysis of the credit risk for portfolios of consumer loans. However, behavioural scores, which are calculated on a monthly basis by most consumer lenders, are the analogues of ratings in corporate credit risk. Motivated by studies of corporate credit risk, we develop a Markov chain model based on behavioural scores for establishing the credit risk of portfolios of consumer loans. Although such models have been used by lenders to develop models for the Basel Accord, nothing has been published in the literature on them. The model which we suggest differs in many respects from the corporate credit ones based on Markov chains — such as the need for a second order Markov chain, the inclusion of economic variables and the age of the loan. The model is applied using data on a credit card portfolio from a major UK bank.     

A mixture model for credit card exposure at default using the GAMLSS framework

The Basel II and III Accords propose estimating the credit conversion factor (CCF) to model exposure at default (EAD) for credit cards and other forms of revolving credit. Alternatively, recent work has suggested it may be beneficial to predict the EAD directly, i.e.modelling the balance as a function of a series of risk drivers. In this paper, we propose a novel approach combining two ideas proposed in the literature and test its effectiveness using a large dataset of credit card defaults not previously used in the EAD literature. We predict EAD by fitting a regression model using the generalised additive model for location, scale, and shape (GAMLSS) framework. We conjecture that the EAD level and risk drivers of its mean and dispersion parameters could substantially differ between the debtors who hit the credit limit (i.e.“maxed out” their cards) prior to default and those who did not, and thus implement a mixture model conditioning on these two respective scenarios. In addition to identifying the most significant explanatory variables for each model component, our analysis suggests that predictive accuracy is improved, both by using GAMLSS (and its ability to incorporate non-linear effects) as well as by introducing the mixture component.     

Measuring Credit Risk of a Bank's Corporate Loan Portfolio Using Advanced Internal Ratings Base Approach

Abstract

The use of technical and advanced approaches in the measurement of credit risk of banks' portfolios has nowadays become a very hot issue. The most recent technical report issued by the Basel Committee in May 2003 has concentrated heavily on the measurement of credit risk using either foundation or advanced Internal Ratings Base (IRB) approaches. This empirical research study attempts to measure credit risk of a bank's corporate loan portfolio, including firms from 10 different Turkish sectors. The monthly observations of the total amount of corporate loans and the total amount of corporate loans at default across various sectors are downloaded from the web page of Central Bank of Turkey (CBT) in a period of 1999-2002. This period covers 47 monthly observations since CBT has captured sectoral corporate loans beginning of 1999. Therefore, the observed sectoral default rates are needed to be simulated to obtain a nicely shaped distribution. Monte Carlo simulation is applied for 1,000 times. Based on the simulated default rates, the expected sectoral default rates are computed. Next, a credit quality rating scale is fitted into sectoral default rates distributions. Finally, the sectoral weights in the whole loan portfolio are multiplied by the expected sectoral default rates matrix, considering cross-sectoral correlations to get the total amount of the bank's credit risk and capital requirement. It is assumed that sectoral monthly default rates are a good representative of the default risk of a sample bank's corporate loan portfolio since no publicly available data on any particular bank's corporate loan portfolio composition exists. Nevertheless, this research may be a good application for measuring the credit risk of banks' corporate loan portfolios using advanced IRB approach.     

What drives credit risk in the Indian banking industry? An empirical investigation

Using a two-step system GMM approach on a unique bank-level dataset for the period 1998/99–2013/14, this paper tries to explore the key determinants of credit risk in the Indian banking industry. The main premise of this paper is that, along with regulatory and institutional factors, both macroeconomic and bank-specific variables influence the formation of credit risk in a banking system, and their influences vary across ownership groups. The empirical findings suggest that lower profitability, more diversification in the banking business, the large size of banks and a higher concentration of banks in lending increase the probability of defaults in India. We find a significant degree of persistence in credit risk, and the observed persistence is higher in the gross non-performing loans (NPLs) specification relative to what has been observed in the net NPLs specification. In the case of public sector banks, NPLs are more sensitive to internal bank-specific factors, while for private and foreign banks, macroeconomic and industry-related factors play a significant role in determining credit risk. Our results are robust for different panel data estimation models and sub-samples of ownership groups. The findings of this paper provide important insights into the formation of default risk in the banking system of an emerging market economy.     

Endogenous trading in credit default swaps

We introduce a real options model in order to quantify the moral hazard impact of credit default swap (CDS) positions on the corporate default probabilities. Moral hazard is widely addressed in the insurance literature, where the insured agent may become less cautious about preventing the risk from occurring. Importantly, with CDS the moral hazard problem may be magnified since one can buy multiple protections for the same bond. To illustrate this issue, we consider a firm with the possibility of switching from an investment to another one. An investor can influence the strategic decisions of the firm and can also trade CDS written on the firm. We analyze how the decisions of the investor influence the firm value when he is allowed to trade credit default contracts on the firm’s debt. Our model involves a time-dependent optimal stopping problem, which we study analytically and numerically, using the Longstaff–Schwartz algorithm. We identify the situations where the investor exercises the switching option with a loss, and we measure the impact on the firm’s value and firm’s default probability. Contrary to the common intuition, the investors’ optimal behavior does not systematically consist in buying CDSs and increase the default probabilities. Instead, large indifference zones exist, where no arbitrage profits can be realized. As the number of the CDSs in the position increases to exceed several times the level of a complete insurance, we enter in the zone where arbitrage profits can be made. These are obtained by implementing very aggressive strategies (i.e., increasing substantially the default probability by producing losses to the firm). The profits increase sharply as we exit the indifference zone.     

Asymmetric convergence in US financial credit default swap sector index markets

This study examines the asymmetric adjustments to the long-run equilibrium for credit default swap (CDS) sector indexes of three financial sectors – banking, financial services and insurance – in the presence of a threshold effect. The results of the momentum-threshold autoregression (M-TAR) models demonstrate that asymmetric cointegration exists for all pairs comprised of those three CDS indexes. The speeds of adjustment in the long-run are much higher in the case of adjustments from below the threshold than from above for all the pairs. The estimates of The MTAR-VEC models suggest that the dual CDS index return in each sector pair participates in the adjustment to equilibrium in the short- and long-run taken together. But in the long-run alone, only one of the two spreads in each pair participates. Policy implications are also provided.     

Fiscal retrenchments and the transmission mechanism of the sovereign risk channel for highly indebted countries

We formalize sovereign and private sector default probabilities into a monetary model in order to test the hypothesis, which recently appeared in the literature, of whether the consideration of a sovereign risk channel affects the sign and size of output fiscal multipliers. The model is estimated for the most vulnerable Eurozone countries-characterized by high debt-to-GDP ratio-and stochastically simulated conditional on expenditure and revenue policy measures. We show that, conditional on specific fiscal shocks, the risk channel can operate in a pro-cyclical direction, amplifying the temporary contractionary effects of fiscal retrenchments. We show that both the relations between economic fundamentals and sovereign debt spreads and that between sovereign and credit spreads are weak. Therefore, the effectiveness of the risk channel for fiscal consolidations is small, irrespective of the direction of change in the sovereign default probability.     

Market perception of sovereign credit risk in the euro area during the financial crisis

We study market perception of sovereign credit risk in the euro area during the financial crisis. In our analysis we use a parsimonious CDS pricing model to estimate the probability of default (PD) and the loss given default (LGD) as perceived by financial markets. In our empirical results the estimated LGDs perceived by financial markets stay comfortably below 40% in most of the samples. Global financial indicators are positively and strongly correlated with the market perception of sovereign credit risk; whilst macroeconomic and institutional developments were at best only weakly correlated with the market perception of sovereign credit risk.     

Quality control for structural credit risk models

Over the last four decades, a large number of structural models have been developed to estimate and price credit risk. The focus of the paper is on a neglected issue pertaining to fundamental shifts in the structural parameters governing default. We propose formal quality control procedures that allow risk managers to monitor fundamental shifts in the structural parameters of credit risk models. The procedures are sequential — hence apply in real time. The basic ingredients are the key processes used in credit risk analysis, such as most prominently the Merton distance to default process as well as financial returns. Moreover, while we propose different monitoring processes, we also show that one particular process is optimal in terms of minimal detection time of a break in the drift process and relates to the Radon–Nikodym derivative for a change of measure.     

Commercial mortgage underwriting: How well do lenders manage the risks?

Loan-to-value ratio and debt service coverage ratios have long been viewed as the two most important quantitative measures of the default risk of commercial mortgages. Option-based models of default provide strong theoretic support for the importance of original loan-to-value ratio. The same theoretical predictions have found strong empirical support in residential single-family mortgage analyses. However, recent empirical studies of commercial mortgage default have raised questions about the role of loan-to-value ratio in assessing the riskiness of commercial mortgages. These studies generally either find no relationship or a puzzling negative relationship between loan-to-value ratio and default. This paper uses a very large database of commercial loan histories to thoroughly investigate this issue. It finds strong evidence that loan-to-value and debt service coverage ratios are endogenous to the underwriting process. Lenders react to other—unmeasured—risk factors with credit rationing and pricing. As a result, unusually low loan-to-value ratio loans appear to have above average risk in other dimensions and their default probabilities are equal to or higher than average. The results show that the pricing spread that lenders establish as part of the underwriting process serves as an excellent summary measure of the riskiness of the loan. A test of lenders’ ability to appropriately price loan-to-value risk finds that, while there is some unpriced effect of loan-to-value ratio after controlling for the lender’s pricing, introducing lender pricing into the model removes the otherwise puzzling negative loan-to-value and default relationship previously observed in the literature.     

Subprime mortgages and the housing bubble

This paper explores the link between the house-price expectations of mortgage lenders and the extent of subprime lending. It argues that bubble conditions in the housing market are likely to spur subprime lending, with favorable price expectations easing the default concerns of lenders and thus increasing their willingness to extend loans to risky borrowers. Since the demand created by subprime lending feeds back onto house prices, such lending also helps to fuel an emerging housing bubble. These ideas are illustrated in a theoretical model, and tentative support is found in empirical work exploring the connection between price expectations and the extent of subprime lending.     

Supply chain finance and impacts of consumers’ sustainability awareness

Several new methods have been proposed for supply chain finance (SCF) with bank credits, but none of them mentions how to solve the borrowers’ moral hazard problems in SCF. This paper examines the moral hazard problem in supply chain financing with procurement contract (or purchase order). We show that since supply chain is an up-down directed structure, when financing with the procurement contract, the supplier’s effort monitoring task can be rendered to the procurement contract, which can secure the supplier’s optimal effort and capital choices in production. Hence, compared to separate lending, the supplier’s credit rationing problem can be mitigated, and most importantly, banks’ under-estimation on the supplier’s default risk and the over-estimation on the retailer’s default risk will both decrease. We further show that the retailer’s corporate social responsibility expenditure can increase consumers’ brand recognition, thus when facing demand shocks arising from consumer’s unexpected concerns, the retailer can better stabilize the firm value.     

Dynamic modeling of regional house price diffusion in Taiwan

This paper examines the lead-lag relationships and the dynamic linkages among four regional house price indices in Taiwan. We employ the Johansen cointegration technique, Toda and Yamamoto’s Granger causality test, the generalized impulse response approach, and variance decomposition analysis to find out the extent and the magnitude of their relationships. The estimated long-run relationship between regional house prices appears to have remained stable throughout the sample period. Our empirical results show a bidirectional relationship between house prices in the most important economic center, Taipei City, and its suburban area, Taipei County. However, there are no causalities of house prices between Taipei City and other megacities in Taiwan. The mutual impacts of the shocks between house prices in Taipei City and Taipei County are significantly positive, while these impacts on Kaohsiung City, far from Taipei City, are insignificant. Finally, the results of the generalized impulse response approach indicate that the house prices indices of Taipei City are the most exogenous while those for Taipei County are the most endogenous.     

Environmental,social and governance disclosure and default risk

We investigate whether environmental, social and governance (ESG) disclosure is related to default risk. Using a sample of US nonfinancial institutions from 2006 to 2017, we find that ESG disclosure is positively related to Merton's distance to default and is negatively related to the credit default swap spread, which suggests that firms with a higher ESG disclosure have lower default risk. Our analysis further indicates that the inverse effect of ESG disclosure on default risk is through increased profitability and reduced performance variability and cost of debt. We also document that the negative impact of ESG disclosure on default risk is existent only for mature and older firms. These results are important for all stakeholders of firms, including shareholders and bondholders to consider firm's ESG disclosure in conjunction with life cycle stage before making their investment decisions.     

UNCOVERING THE COMMON RISK‐FREE RATE IN THE EUROPEAN MONETARY UNION

We introduce longitudinal factor analysis (LFA) to extract the common risk‐free (CRF) rate from a sample of sovereign bonds of countries in a monetary union. Since LFA exploits the typically very large longitudinal dimension of bond data, it performs better than traditional factor analysis methods that rely on the much smaller cross‐sectional dimension. European sovereign bond yields for the period 2006–2011 are decomposed into a CRF rate, a default risk premium and a liquidity risk premium. Our empirical findings suggest that investors chase both credit quality and liquidity, and that they price double default risk on credit default swaps. Copyright © 2013 John Wiley & Sons, Ltd.     

Renter Mobility and Multifamily Mortgage Default Risk

Renter mobility is a major concern for the performance of multifamily mortgages. If enough new renters are not found to replace those that move, vacancy rates can quickly escalate to where cash flows are negative and property mortgages are in jeopardy. In this study we examine how differences in renter mobility patterns by property type can affect mortgage credit risk within submarkets of an MSA. We expand the default model developed by Goldberg and Capone (2000) to use unique distributions of rental unit turnover and vacancy durations for large and small multifamily rental properties. Monte Carlo simulations then show how credit risk on multifamily mortgages is affected if owners of small properties are able to keep tenants longer than owners of larger properties can. The model can be used to explore other potential intra-MSA differences in property market dynamics.