Chiara Pederzoli

Stochastic Volatility and GARCH: a Comparison Based on UK Stock Data

This paper compares two types of volatility models for returns, ARCH-type and stochastic volatility (SV) models, both from a theoretical and an empirical point of view. In particular a GARCH(1,1) model, an EGARCH(1,1) model and a log-normal AR(1) stochastic volatility model are considered. The three models are estimated on UK stock data: a series of the British equity index FTSE100 is used to estimate the relevant parameters. Diagnostic tests are implemented to evaluate how well the models fit the data. The models are used to obtain daily volatility forecasts and these volatilities are used to estimate the “VaR” on a simple one-unit position on FTSE100. The VaR accuracy is tested by means of a backtest. While the results do not lead to a straightforward preference between GARCH(1,1) and SV, the EGARCH shows the best performance.

Forward-looking Estimation of Default Probabilities with Italian Data

The solution adopted in Basel II to deal with procyclicality of capital requirements (i.e. through the cycle ratings and long-run average estimates of default probabilities) implies a reduction in the risk-sensitivity that contradicts the original spirit of the new framework.In order to preserve risk-sensitivity and to dampen procyclicality at the same time, Pederzoli and Torricelli (2005) set up a model which relies on a business cycle forecast in the estimation of the default probability and provide an application for the US. The modelling approach hinges on a forward-looking definition of capital requirements, in anticipation of the business cycle with a possible smoothing effect on the business cycle turning points.The present paper checks the robustness of the approach for the Italian case, where alternative business cycles chronologies are used and ratings have to be approximated by exploiting default data provided by the Bank of Italy. Findings suggest that the comparison between the alternative chronologies is an important issue.

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

Recent years witnessed commodity prices increases which have fostered research works on their predictability and a renewed interest of practitioners and policy-makers. The objective of this article 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 Chicago Board of Trade (CBOT) in the period May 1998 to 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.

The Interaction of Financial Fragility and the Business Cycle in Determining Banks Loan Losses: An Investigation of the Italian Case

The Basel II capital accord and the recent crises have fostered the debate over the financial stability of the aggregate banking sector. Because loan losses are an important factor for banking stability, this paper aims to gauge the impact of real and financial fragility on default losses of Italian banks. To this end the ratio of non-performing loans to total loans is regressed on the business cycle and indebtedness. In addition, to capture the joint effect of real and financial fragility, the analysis considers an interaction term, which to our knowledge has never been applied before to Italian default data. Based on the interaction model, results show that the actual impact of financial fragility on default losses depends not only on the business cycle phase but also on the firms size, whereby in adverse economic conditions, small firms are more significantly affected by financial fragility.

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.

Banks' optimal rating systems and procyclicality

The introduction of Basel II has rised concerns about the possible impact of risk-sensitive capital requirement on the business cycle. Several approaches have been proposed to deal with the procyclicality issue: a general equilibrium model is an appropriate framework for a comprehensive analysis of different proposals since it allows to account for banks endogenous strategies in relation to the other agents’ behaviour. The set up of a model to evaluate different rating systems in relation to the procyclicality issue is presented. [ DOI : 10.1685/CSC06147] About DOI