Optimization Heuristics for Determining Internal Rating Grading Scales

Basel II imposes regulatory capital on banks related to the default risk of their credit portfolio. Banks using an internal rating approach compute the regulatory capital from pooled probabilities of default. These pooled probabilities can be calculated by clustering credit borrowers into different buckets and computing the mean PD for each bucket. The clustering problem can become very complex when Basel II regulations and real-world constraints are taken into account. Search heuristics have already proven remarkable performance in tackling this problem as complex as it is. A Threshold Accepting algorithm is proposed, which exploits the inherent discrete nature of the clustering problem. This algorithm is found to outperform alternative methodologies already proposed in the literature, such as standard k-means and Differential Evolution. Besides considering several clustering objectives for a given number of buckets, we extend the analysis further by introducing new methods to determine the optimal number of buckets in which to cluster banks' clients.credit risk, probability of default, clustering, Threshold Accepting, Differential Evolution

Optimization Heuristics for Determining Internal Rating Grading Scales

Basel II imposes regulatory capital on banks related to the default risk of their credit portfolio. Banks using an internal rating approach compute the regulatory capital from pooled probabilities of default. These pooled probabilities can be calculated by clustering credit borrowers into different buckets and computing the mean PD for each bucket. The clustering problem can become very complex when Basel II regulations and real-world constraints are taken into account. Search heuristics have already proven remarkable performance in tackling this problem as complex as it is. A Threshold Accepting algorithm is proposed, which exploits the inherent discrete nature of the clustering problem. This algorithm is found to outperform alternative methodologies already proposed in the literature, such as standard k-means and Differential Evolution. Besides considering several clustering objectives for a given number of buckets, we extend the analysis further by introducing new methods to determine the optimal number of buckets in which to cluster banks' clients.credit risk, probability of default, clustering, Threshold Accepting, Differential Evolution

Optimization Heuristics for Determining Internal Rating Grading Scales

Basel II imposes regulatory capital on banks related to the default risk of their credit portfolio. Banks using an internal rating approach compute the regulatory capital from pooled probabilities of default. These pooled probabilities can be calculated by clustering credit borrowers into different buckets and computing the mean PD for each bucket. The clustering problem can become very complex when Basel II regulations and real-world constraints are taken into account. Search heuristics have already proven remarkable performance in tackling this problem. A Threshold Accepting algorithm is proposed, which exploits the inherent discrete nature of the clustering problem. This algorithm is found to outperform alternative methodologies already proposed in the literature, such as standard k-means and Differential Evolution. Besides considering several clustering objectives for a given number of buckets, we extend the analysis further by introducing new methods to determine the optimal number of buckets in which to cluster banks’ clients

A test of the Behavioral versus the Rational model of Persuasion in Financial Advertising

We present a test of the behavioral versus the rational model of advertising in the financial market. We analyze the Granger-causality relationship existing between Comit stock market index and advertising of financial products and services from the most important daily published financial newspaper in Italy. We run the test for both the risky and non-risky advertising, finding that the behavioral model of advertising is supported when risky financial products and services are considered, while the rational model is true for the non-risky. We ascribe this result to the dual process of reasoning: When investors evaluate the decision to buy risky financial products and services, they activate the automatic, rapid decision making process. The behavioral model of advertising copes with it and provides an advertising strategy that responds to market evolutions. When non-risky financial products and services are considered, a different mental process, requiring slow and sequential reasoning, operates, compatibly with a rational decision making process

Threshold Accepting for Credit Risk Assessment and Validation

According to the latest Basel framework of Banking Supervision, financial institutions should internally assign their borrowers into a number of homogeneous groups. Each group is assigned a probability of default which distinguishes it from other groups. This study aims at determining the optimal number and size of groups that allow for statistical ex post validation of the efficiency of the credit risk assignment system. Our credit risk assignment approach is based on Threshold Accepting, a local search optimization technique, which has recently performed reliably in credit risk clustering especially when considering several realistic constraints. Using a relatively large real-world retail credit portfolio, we propose a new technique to validate ex post the precision of the grading system.credit risk assignment, Threshold Accepting, statistical validation

Are defined contribution pension schemes socially sustainable? A conceptual map from a macroprudential perspective

If the combined retirement income, provided by public and private defined contribution (DC) pension schemes, falls below socially acceptable standards, there is a political risk that consensus seeker policymakers could yield to pressures to commit future fiscal revenues. These contingent liabilities, when incorporated in markets\u2019 expectations, are bound to create spillovers on sovereign risk, with negative feedback loops on the capital adequacy of banks and of other intermediaries, owing to losses on their government paper. Among the causes of reduced annuities out of the final assets in DC pension funds is an equity risk premium much lower than the commonly values advertised by the industry and by policymakers. From a macroprudential perspective, this political risk should be taken into account in stress tests assessing banks\u2019 resilience to financial shocks

Corridor implied volatility and the variance risk premium in the Italian market

Corridor implied volatility introduced in Carr and Madan (1998) and recently implemented in Andersen and Bondarenko (2007) is obtained from model-free implied volatility by truncating the integration domain between two barriers. Corridor implied volatility is implicitly linked with the concept that the tails of the risk-neutral distribution are estimated with less precision than central values, due to the lack of liquid options for very high and very low strikes. However, there is no golden choice for the barriers levels’, which will probably change depending on the underlying asset risk neutral distribution. The latter feature renders its forecasting performance mainly an empirical question. The aim of the paper is twofold. First we investigate the forecasting performance of corridor implied volatility by choosing different corridors with symmetric and asymmetric cuts, and compare the results with the preliminary findings in Muzzioli (2010b). Second, we examine the nature of the variance risk premium and shed light on the information content of different parts of the risk neutral distribution of the stock price, by using a model-independent approach based on corridor measures. To this end we compute both realised and model-free variance measures which accounts for drops versus increases in the underlying asset price. The comparison is pursued by using intra-daily synchronous prices between the options and the underlying asset.corridor implied volatility, variance swap, corridor variance swap, variance risk

Modelling credit risk for innovative firms: the role of innovation measures

Financial constraints are particularly severe for R&D projects of SMEs, which cannot generally rely on equity markets and, in the EU, on a sufficiently developed VC industry. If innovative SMEs have to depend on banks to finance their R&D projects, it is particularly important to develop models able to estimate their probability of default (PD) in consideration of their peculiar features. Based on the signaling value of some innovative assets, the purpose of this paper is to show the importance to include them into models which have proved to be successful for SMEs. To this end, we take a logit model and test it on a unique dataset of innovative SMEs (based on PATSTAT database, EPO BULLETIN and AMADEUS) to estimate a two-year PD with default years 2006-2008. In the regression analysis the innovation-related variables are two in order to account for R&D productivity at the level of the firm and to consider the value of the inventive output. Our analyses first address measurement issues concerning innovation-related variable and then show that, while the accounting variables and the patent value are always significant with the expected sign, the patent number per se reduces the PD only in the presence of an appropriate equity level.innovative SMEs; default probability; patent value

Systemic risk measures and macroprudential stress tests An assessment over the 2014 EBA exercise

The European Banking Authority (EBA) stress tests, which aim to quantify banks’ capital shortfall in a potential future crisis (adverse economic scenario), further stimulated an academic debate over systemic risk measures and their predictive/informative content. Focusing on marked based measures, Acharya et al. (2010) provides a theoretical background to justify the use of Marginal Expected Shortfall (MES) for predicting the stress test results, and verify it on the first stress test conducted after the 2007-2008 crises on the US banking system (SCAP, Supervisory Capital Assessment Program). The aim of this paper is to further test the goodness of MES as a predictive measure, by analysing it in relation to the results of the 2014 European stress tests exercise conducted by EBA. Our results are strongly dependent on index used to capture the systemic distress event, whereby MES, based on a global market index, does not show association with EBA stress test, by contrast to F-MES, which is based on a financial market index, and has a significant information and predictive power. Our results may carry useful regulatory implication for the stress test exercises

Efficiency and unbiasedness of corn futures markets: New evidence across the financial crisis

Recent years witnessed commodity prices increases which have fostered researchworks on their predictability and a renewed interest of practitioners and policy makers. The objective of this paper is to test the predictive ability of futures prices on the underlying spot prices by taking corn, which is one of the most important agricultural commodities in terms of trading volumes and for its role in the dietary regime of many countries. We consider the corn futures on the CBOT in the period May 1998-December 2011 so as to extend previous studies on this market and to assess a possible effect of the financial crisis. Our results do not emphasize a role for the latter and, although we do not find evidence of efficiency and unbiasedness, the futures corn price turns out to be the best predictor of the spot price if compared with most used alternatives