Mario Anolli

Are European Banks Too Big? Evidence on Economies of Scale

In light of the policy debate on too-big-to-fail we investigate evidence of economies of scale for 103 European listed banks over 2000–2011. Using the Stochastic Frontier Approach, the results show that economies of scale are widespread across different size classes of banks and are especially large for the biggest banks. At the country level, banks operating in the smallest financial systems and the countries most affected by the financial crises realize the lowest scale economies (including diseconomies) due to the reduction in production capacity. As for the determinants of scale economies, these mainly emanate from banks oriented toward investment banking, with higher liquidity, lower Tier 1 capital, those that contributed less to systemic risk during the crises, and those with too-big-to-fail status.

Italian Open End Mutual Fund Costs

We investigate the costs investors incur when they hold shares of Italian open end mutual funds. The overall explicit cost can range from less than 50 to well over 250 basis points in terms of assets under management. Nevertheless, mutual funds investors seem to be almost unaware of the importance of costs and tend to focus mainly on the net return when making their investment decisions. We measure the overall costs of a large sample of mutual funds managed by Italian intermediaries in the period 2000-2003 and also evaluate the determinants of cost efficiencies for the period 2000-2003.

Internalization in European Equity Markets Following the Adoption of the EU Mifid Directive

The European Unions Markets in Financial Instruments Directive (MiFID), that will be implemented by October 2007, significantly modifies the regulation of the European securities industry. It will allow, among other things, investment firms to act as systematic internalizers. A systematic internalizer is an investment firm dealing on its own account to execute client orders outside a regulated market or a multilateral trading facility (MTF). Specifically, the new regulation requires systematic internalizers to publish firm quotes on liquid shares when dealing for retail quantities. In short, systematic internalizers are market makers on liquid stocks who execute small trades. This paper uses order flow and limit order book data in order to estimate the internalization rate (i.e., the portion of the total order flow that could be internalized), to estimate the internalization expected revenues, and to investigate the main factors affecting both the internalization rate and the magnitude of internalization revenues. To simulate the systematic internalization activity we collected detailed order flow data for 57 liquid stocks traded on the Italian Stock Exchange, which is a currently concentrated market. To be internalized, an order should jointly satisfy the following two requirements (expressly requested by the Level 1 law text). First, the quantity of the order should not be greater than the estimated standard market size (SMS). Second, the price limit of the order should be compatible with immediate execution by a systematic internalizer in respect of the best execution principle. Based on this procedure we identify internalized orders and compute estimates of internalization rate, gross trading revenues, spread revenues and positioning revenues on a per stock per day basis and on a per internalizer firm per day basis. Our main findings relate to (i.) the relationship between internalization rates and stocks turnover; (ii.) the size and variability of internalization trading revenues; (iii.) the value of the inventories for an internalizer firm.

Retail Credit Risk Management

List of Tables List of Figures Notes on Contributors PART 1 REGULATORY FRAMEWORK Introduction Anolli, M., Beccalli, E. PART 2 RISK TAKING: MEASUREMENT, PRICING AND MANAGEMENT The Ever-evolving Basel Accord Guadalupi, D. Private Individuals: Credit Risk Modeling Giannasca, C., Giordani, T. SMEs: Credit Risk Modeling Giovannini, E. The Critical Model Parameter: LGD Alghisi Manganello, E., Leucari, V. Model Validation Arfe, A., Gianturco, P. Risk Adjusted Performance Measures Anolli, M. PART 3 PORTFOLIO CREDIT RISK: MEASUREMENT AND MANAGEMENT Portfolio Credit Risk Modeling Bocchi, L., Bellini, T. Stress Testing, Capital Planning, and Risk Integration Bellini, T, Bocchi, L. Portfolio Management Giordani, T., Giannasca, C. PART 4 OPERATIONAL IMPLICATION IT Systems for Credit Risk Management Traversini, R., Marmonti, A. A New Retail Credit Risk Management Approach to Cope with the Crisis Merlin, F.

Bank Risk and Analysts’ Forecasts

The financial crisis has highlighted, inter alia, that the financial community as a whole suffered from important limitations and distortions in the perception of risk faced by banks. The distortion materialized in a marked underestimation of risk by the major players in the system: top management, board of directors, rating agencies, regulatory and supervisory authorities, and so on.