Collections policy comparison in LGD modelling

This paper discusses the similarities and the differences in the collection process between in house and 3rd Party collection. The objective is to show that although the same type of modelling approach to estimating Loss Given Default (LGD) can be used in both cases the details will be significantly different. In particular the form of the LGD distribution suggests one needs to split the distribution in different easy in the two cases as well as using different variables. The comparisons are made use two data sets of the collections outcomes from two sets of unsecured consumer defaulters<br/

Forecasting bank loans loss-given-default

With the advent of the new Basel Capital Accord, banking organizations are invited to estimate credit risk capital requirements using an internal ratings based approach. In order to be compliant with this approach, institutions must estimate the expected loss-given-default, the fraction of the credit exposure that is lost if the borrower defaults. This study evaluates the ability of a parametric fractional response regression and a nonparametric regression tree model to forecast bank loan credit losses. The out-of-sample predictive ability of these models is evaluated at several recovery horizons after the default event. The out-of-time predictive ability is also estimated for a recovery horizon of one year. The performance of the models is benchmarked against recovery estimates given by historical averages. The results suggest that regression trees are an interesting alternative to parametric models in modeling and forecasting loss-given-default.Loss-given-default, Forecasting, Bank loans, Fractional response regression, Regression trees

Application of Stationary Wavelet Support Vector Machines for the Prediction of Economic Recessions

This paper examines the efficiency of various approaches on the classification and prediction of economic expansion and recession periods in United Kingdom. Four approaches are applied. The first is discrete choice models using Logit and Probit regressions, while the second approach is a Markov Switching Regime (MSR) Model with Time-Varying Transition Probabilities. The third approach refers on Support Vector Machines (SVM), while the fourth approach proposed in this study is a Stationary Wavelet SVM modelling. The findings show that SW-SVM and MSR present the best forecasting performance, in the out-of sample period. In addition, the forecasts for period 2012-2015 are provided using all approaches

Macroeconomic determinants of bad loans: evidence from Italian banks

In this paper we use a single-equation time series approach to examine the macroeconomic determinants of banks’ loan quality in Italy in the past twenty years, as measured by the ratio of new bad loans to the outstanding amount of loans in the previous period. We analyse the quality of loans to households and firms separately on the grounds that macroeconomic variables may affect these two classes of borrowers differently. According to our estimated models: i) the quality of lending to households and firms can be explained by a small number of macroeconomic variables mainly relating to the general state of the economy, the cost of borrowing and the burden of debt; ii) changes in macroeconomic conditions generally affect loan quality with a lag; and iii) the out-of-sample prediction accuracy of the models is quite satisfactory and proved to be robust to the recent financial crisis.bad loans, macroeconomic determinants, Italian banking system

Assessing the Currency Crises in Turkey

This study presents the significance of the currency crises, discusses the related literature and applies a model of economic vulnerability to Turkey during 1985Q2-2004Q2. The common approach in currency crisis literature is to focus on the performance of thresholds for a set of early warning indicators. Following the explanation of “Index of Speculative Pressure” (ISP), Granger causes of the ISP is discussed. The study shows that, current account/ GDP ratio, M2/international reserves ratio, real credit growth and current account/foreign direct investment ratio are Granger causes of the ISP at 1% level. Then by using Vector Auto Regression (VAR) model, the ISP index is forecasted. The study shows that the combination of VAR(1)+VAR(2)+VAR(5) models generate relatively better forecast values than all other single models. Finally the study estimates dynamic probit and logit models by using maximum likelihood to predict currency crises. It shows that logit model gives a better performance than the probit, for a better prediction of the probabilities of the Turkish currency crises. The most important contribution of this study is to show that the logit model has a very high performance in the prediction of Turkish currency crises. It can be used to foresee forthcoming currency crises. Also the forecast of the ISP (as a level) is giving very successful results. It is observed that the ISP and forecasted ISP values are almost moving together or very close to each other.Currency Crises, Speculative Pressure, Exchange Rates, Financial Crises

The Application of Neural Networks to the Pricing of Credit Derivatives

The present paper deals with a new approach to the pricing of credit derivatives, which are innovative financial instruments able to immunize a securities portfolio from the default risk of the issuers, using neural networks. After an essential analysis of the most important topics inherent to these nonlinear statistical instruments, particular emphasis, due to their diffusion, has been put on the characters of Credit Default Swaps and on the particularities of the structural and reduced form approaches proposed for their analysis. In the final part of the paper the effectiveness of neural networks in approximating the evaluation of credit derivatives and in improving the timing in the default prevision is illustrated.

On credit spread slopes and predicting bank risk

The authors examine whether credit-spread curves, engendered by a mandatory subordinated-debt requirement for banks, would help predict bank risk. They extract the credit-spread curves each quarter for each bank in our sample, and analyze the information content of credit-spread slopes. They find that credit-spread slopes are significant predictors of future credit spreads. However, credit-spread slopes do not provide significant additional information on future bank-risk variables, over and above other bank-specific and market-wide information.Bank capital ; Risk

Making Explosive Cocktails: recipes and costs for 26 Crises from 1823 to 2003

Crises, like “explosive cocktails” are made by mixing powerful ingredients. Argentina has made 26 “explosive cocktails” since 1823. How many ingredients are needed to make an “explosive cocktail”? Which are these ingredients? Which is the most expensive mix? This paper attempts to identify the different recipes that ended up in economic crisis throughout argentine economic history by means of the regression tree analysis technique. The paper also measures Argentina’s crises costs in terms output losses. We follow the methodology used by the IMF (1998), that is, computing cumulative output lost relative to trend. It is found that there are four explosive mixes, having Fiscal Deficit, Real Exchange Rate Overvaluation, Bank Deposit growth rate decline and the ratio of External Debt to Exports as the key ingredients. The most frequent crises are those having high fiscal deficit; though average cost is higher for crises mixing moderate fiscal with strong decline in Real Bank Deposits, presumably entailing banking crises.Currency Crises, Regression Tree Analysis, Crises Costs

The economics of rating watchlists: evidence from rating changes

Generally, information provision and certification have been identified as the major economic functions of rating agencies. This paper analyzes whether the “watchlist" (rating review) instrument has extended the agencies' role towards a monitoring position, as proposed by Boot, Milbourn, and Schmeits (2006). Using a data set of Moody's rating history between 1982 and 2004, we find that the overall information content of rating action has indeed increased since the introduction of the watchlist procedure. Our findings suggest that rating reviews help to establish implicit monitoring contracts between agencies and borrowers and as such enable a finer partition of rating information, thereby contributing to a higher information quality

Acquisition Values and Optimal Financial (In)Flexibility

In this paper, the authors analyze optimal financial structure for an incumbent and potential entrant accounting for feedback effects in secondary asset markets.Financial Flexibility; Market Entry; Acquisition; Exit Values; Predation; Financial Contracting; Product Market Competition