Credit scoring: Does XGboost outperform logistic regression?A test on Italian SMEs

The old-fashioned logistic regression is still the most used method for credit scoring. Recent developments have evolved new instruments coming from the machine learning approach, including random forests. In this paper, we tested the efficiency of logistic regression and XGBoost methods for default forecasting on a sample of 35,535 cases from 7 different business sectors of Italian SMEs, on a set of 28 banking variables and 55 balance sheet ratios for verifying which approach is better supporting the lending decisions. With this aim, we developed an efficiency index for measuring each model's capability to correctly select good borrowers, balancing the different effects of refusing the loan to a good customer and lending to a defaulter. Also, we computed the balancing spread to quantify the different models' efficiency in terms of credit costs for the borrower firms. Results show that different sectors report different results. However, generally speaking, the two methods report similar capabilities, while the cutoff setting can make a substantial difference in the actual use of those models for lending decisions

CR-relatives Kähler manifolds

In this paper we show that two Kähler manifolds which do not share a Kähler submanifold, do not share either a Levi degenerate CR–submanifold with constant dimension Levi kernel. In particular, they do not share a CR–product. Further, we obtain that a Levi degenerate CR-submanifold of C^n cannot be isometrically immersed into a flag manifold

Modeling and simulating cross country banking contagion risks

The recent financial crisis proved that financial contagion could spread among countries resulting in disruptive effects. In this paper, by modeling and simulating banking system behavior and linkages across countries, we assess, based on data from the BIS and IMF, the possible outcome of domestic crises and how contagion spreads over countries. Results allow detailing the role of a "lighter" or of a "fueler" of financial crises for each country and assessing how each country can affect each other country by contagion, signaling the importance of financial interdependence between some neighboring countries, and detailing which counterpart country would be affected by the ring-fencing of each considered country's banking system. The method also allows for what-if analyses to optimize the risk exposures, and to plan an emergency strategy in case of alarms coming from specific countries

A simulation approach to distinguish risk contribution roles to systemic crises

The last financial crisis has shown that large banking crises pose a highly dangerous risk to both the real economy and public finances. Reducing that risk has become a priority for regulators and governments, but the debate on how to deal with it remains open. Contagion plays a key role: domino effects can turn a relatively small difficulty into a systemic crisis. It is thus important to assess how contagion spreads across banking systems and how to distinguish the two roles played by ‘lighters’ and ‘fuel’ in the crisis, i.e. which banks are likely to start financial contagion and which have a ‘passive’ role in just being driven to default by contagion. The aim of this paper is to propose a methodology for distinguishing the two roles, and for assessing their different contributions to systemic crises. For this purpose, we have adapted a Monte Carlo simulation-based approach for banking systems which models both correlation and contagion between banks. Selecting large crises in simulations, and finding which banks started each simulated crisis, allows us to distinguish ‘primary’ and ‘induced’ defaults and fragility, and to determine the contribution of individual banks to the triggering of systemic crises. The analysis has been tested on a sample of 83 Danish banks for 2010.JRC.G.1-Scientific Support to Financial Analysi

Using Supra-Covered Bonds to Enhance Liquidity in the Euro Area: Assessment of Advantages for the Banking Sector

The discussion on the necessity of a larger volume of very highly quality liquid assets (VHQLA) in the euro area has been very extensive. The debate on expanding the pool of comparable euro area assets focuses on “safe assets”, often on various combinations of government bonds, most of which would not entail a strong increase in euro VHQLA. This paper explores a dierent option, complementary to the existing ones, based on the creation of a safe European asset backed by fully private assets. The paper proposes the issuance of supra-covered bonds by a central European institution. The latter are bonds issued by the central issuer and backed by covered bonds, which banks would have created using their mortgages as their cover pool. The aim is to increase substantially the outstanding amount of euro VHQLA. Such an asset would also be very beneficial during crisis periods, such as the current COVID19 crisis, by allowing banks to transform mortgages into very high quality liquid assets that can be used for funding and as a collateral in operations with the Eurosystem, thus enhancing the possible credit to sustain small and medium-sized enterprises (SMEs). This paper assesses the main eects of such a proposal on banks under dierent possible scenarios

Exploiting the European Volatility Index Features: Anti-Persistence, Skewness, Kurtosis, and the Role of the Hurst Exponent

Volatility indices are fundamental in the study of stock markets. In this paper, we analyzed the classical statistical characteristics of the main volatility index of the European stock markets (VStoxx) and evidenced some interesting connections and cause-effect relationships between the Hurst exponent and the moments of the distribution. Our results suggest that the market volatility is characterized by anti-persistence and mean reversion and that the Hurst exponent variations seem to anticipate the variations of the other moments of the distribution such as skewness and kurtosis, so that the Hurst exponent variations can possibly signal near-term market reversals

Are Banks Still a Risk Source for Stock Market? Some Empirical Evidences

The global financial crisis of 2008 proved that what initially appeared to be relatively small losses in the financial system can be magnified to systemic ones. The European Union debt crisis has thus revived interest in the interdependence across different markets, especially sovereign debt markets and the banking sector, and in the interlinkages among idiosyncratic and common shocks. This paper analyzes the evolution over time of the incidence of common shocks on the main Italian banking groups starting from the period of European Central Bank’s Quantitative Easing program. Results show that the banking sector is no longer perceived by the markets as a common risk source, overcoming the negative picture coming from the financial crisis of 2008–2009. The analysis also suggests that the common risk is broadly affected by the ECB monetary policy, and the idiosyncratic risk is linked to the recapitalization processes

European deposit guarantee schemes: revision of risk based contributions using CDS spreads

Deposit Guarantee Schemes (DGS) aim at protecting depositors of all credit institutions against bank failures. One of the most critical issues about DGS concerns the criteria to be used to assess the risk‐based contribution that each member bank should pay to the Scheme. We propose an alternative model for risk-based contributions based on CDS spreads. We construct the same balance sheet ratios used in the Italian DGSs for a sample of EU banks issuing CDSs. Subsequently we perform panel regressions to explore the relationship between CDS spreads and balance sheet indicators. Results are used to construct an Aggregate Indicator of bank riskiness that is compared with the Aggregate Indicator currently used in the analyzed DGS.JRC.G.1-Scientific Support to Financial Analysi

The Role of Contagion in Financial Crises: an Uncertainty Test on Interbank Patterns

The main lesson learned from the recent financial crisis is the crucial role of interconnectedness between banks as a factor that can push the effects of bank defaults to extreme levels. One bank in distress can compromise the ability to repay obligations of its creditor banks, thereby inducing a more general crisis that spreads from the banking system towards the real economy. Several empirical and theoretical studies have focused on the role of the interbank market in causing contagion in financial crises. In this regard, one frequent problem encountered in dealing with contagion risk in the banking system is that only data on interbank credits and debts aggregated at bank level are publicly available, whereas the whole matrix of interbank linkages would be needed in order to estimate systemic risk correctly. One common solution is to assume that banks maximise the dispersion of their interbank credits and debts, so that the interbank matrix can be approximated by its maximum entropy. This paper tests the influence of this hypothesis on simulations by verifying if variations in the structure of the interbank matrix lead to significant changes in the magnitude of contagion. In order to do this, an algorithm was developed that generates interbank matrices with higher concentration. Then a Monte Carlo simulation was run by making use of the SYMBOL model (SYstemic Model of Banking Originated Losses) jointly developed by the JRC, DG MARKT, and experts of banking regulation (see De Lisa et al., 2010). We than compared results obtained using the maximum entropy approximated matrix with those obtained from more concentrated matrices. Numerical experiments, performed on samples of banks from four European countries, highlight that concentration in interbank loans does affect results but that, when considering the probability distribution of losses, even significant changes in the interbank matrix do not deeply affect results.JRC.G.1-Scientific Support to Financial Analysi

The mitigation role of collaterals and guarantees under Basel II

Under the Basel II framework for capital adequacy of banks, regulatory financial collateral and guarantees (C&G ) can affect lending policy in both a micro and a macro perspective. This paper aims at assessing these effects throught the modelling of the impact of C&G on credit spreads. In doing this we assume the perspective of a bank adopting a Foundation Internal Rating Based approach to measure credit risk and we apply a comparative-static analysis to a pricing model, based on the intrinsic value pricing approach as in the loan arbitrage-free pricing model (LAFP) suggested by Dermine (1996). Our results show that financial collaterals are more effective than guarantees in reducing credit spreads, this differential impact becoming greater as the borrower’s rating worsen. Moreover, the effects of C&G on credit spreads can be more effective than an improvement of borrower’s rating, this possibly leading to negative outfits on credit industries’ allocative efficiency.JRC.G.1-Scientific Support to Financial Analysi