A Network Analysis of the Italian Overnight Money Market

published in "Journal of Economic Dynamics and Control", 2008, co-authored with Giulia Iori, Giulia de Masi, Ovidiu Precup and Giudo Caldarelli

The objective of this paper is to analyze, by employing methods of statistical mechanics of complex networks, the network topology of the Italian segment of the European overnight money market.
We investigate differences in the activities of banks of different size and the evolution of their connectivity structure over the maintenance period. The main objectives are to understand potential implications of current institutional arrangements on the stability of the banking system and to assess the efficiency of the interbank market in terms of absence of speculative and preferential trading relationships.

Which Factors Affect Corporate Bond Pricing? Evidence from Eurobonds Primary Market Spreads

published in "European Journal of Finance", 2005, co-authored with Andrea Sironi

The question of which factors are relevant in determining corporate bonds pricing is empirically investigated by analyzing the issuance spreads of eurobonds completed by Canadian, European, Japanese and U.S. companies during the 1991-2001 eleven year period. A unique dataset of spreads, ratings and other relevant bond variables is used for a sample of 3,403 eurobonds issues. Four main results emerge from the empirical analysis. First, the ratings of corporate bonds are the most important determinant of spreads between the yield to maturity of bonds and that of equivalent Treasury securities. Second, bond investors' reliance on rating agencies judgements has increased over time during the sample period. Third, while a bond's expected tax treatment represents a relevant factor explaining spreads cross-sectional variability, the primary market efficiency and the expected secondary market liquidity appear as poor explanatory variables. Finally, empirical evidence shows that rating agencies adopt a different, "through the cycle" evaluation criteria of obligors' creditworthiness with respect to the forward looking one adopted by bond investors

A Survey on Risk Management and Usage of Derivatives by Non-Financial Italian Firms

co-authored with Gordon M. Bodnar, Costanza Consolandi, Ameeta Jaiswal-Dale

This paper presents a survey on the risk management function and the usage of hedging instruments by Italian non-financial firms. The objective is to measure how firms manage the following risks: Exchange-foreign, Interest rate, Energetic, Commodity, Equity, Counter-party, Operational, Country. The survey was conducted both for listed and non-listed firms, suggest that Italian firms are less likely to use derivatives than US firms. The percentage of firms using derivatives or insurance instruments has not changed noticeably in the last 10 years. The use of derivatives is more significant among large firms in every risk typology. The reasons to explain the limited practice in derivative markets are the insufficient exposure to risk area to warrant management, the exposure more effectively managed by other means and the difficulties in monitoring/measuring contract effectiveness.

The Liquidity Risk Factors for Bonds

co-autored with B. Salis

The main purpose of the paper is to define a model to estimate the liquidity risk for bonds, since very frequently their volatility price is lower than what appears after some shocks. The expected output will be generated comparing qualitative and quantitative methodologies, such as bond portfolio managers and statistical analysis.
The explaining variables for bond liquidity risk are: currency, exchange, issue date, maturity, coupon type, coupon, duration, yield, rating Moody, rating S&P, default, outstanding, and, finally, the existence of some options.
The main factors which lead to the estimation of liquidity risk are whether the bonds are listed, the default of the bond and maturity.
The fitting of the model is measured comparing theoretical outcomes with the qualitative indications of some senior portfolio managers.

Keywords: Liquidity risk, corporate bond, discriminant analysis, logit
JEL Classifications: G11, G12

Time Diversification and Financial Forecasts for Bond and Equity Markets

Depending tactical asset allocation upon the forecasting model choice, it is often discussed the existence of a time diversification opportunity. We focus the analysis on MSCI and JPMorgan benchmarks for equity and fixed income market in Italy, Switzerland, UK, Europe, USA, Japan, and Far East. The topic of this paper consists on the comparison of three methods to estimate the risk premium: the historical return, the building block and the CAPM, which help to optimise asset allocation decisions through different holding periods. Time series have been chosen in order to avoid structural breaks, recorded after 2000. We give an answer to some relevant questions (i) how long risk premiums take to become stable among reliable intervals? (ii) is it possible to define ex-ante criteria to choose forecasting and time diversification methods? We demonstrate how forecasts efficacy change through different holding periods; moreover, historical returns start loosing their (slight) ability to estimate the expected ones with lower holding periods than already experimented in literature. The second result is that reliability ranking depends on the preference for a time horizon.

Keywords: asset allocation, investment horizon effect, financial forecasting, equity, bond, investment risk

JEL Classifications: G11

Emission Trading Scheme and the Price of Energy

This research analyzes the relationship between the carbon and the energy market. These two markets are linked together on a regulatory and on a structural basis. The energy sector is the most important industry within the European Emission Trading Scheme (EU ETS): as main producers of carbon emissions they are also the main users of carbon allowances. The question we address here is if there is a direct link between the carbon spot market and the energy spot market. We investigate the correlation, called pass through rate (PTR) between the energy and carbon market. Our findings show that the PTR is extremely volatile, and it depends on time frame and purposes of the energy market players. This leads to an intervention by policy makers and regulators to define the rules framework of the EU ETS.

Keywords: Emission Trading Scheme, Correlation, Energy, Pass Through Rate

JEL Classifications: G32, Q47

Compliance Risk in the Evolution of the Investment Services - Characteristics, Control Tools and Organizational Issues

co-authored with Paola Musile Tanzi, Daniele Previati, Paola Schwizer

This research has looked at the present state and the progressive scenario of how banks and investment companies have put compliance into practice. It is the first time that in an empirical investigation, the subject of compliance risk focuses on the advancement of investment services, as defined by the Directive 2004/39/CE: 1) reception and transmission of order in relation of one or more financial instruments; 2) execution of orders on behalf of clients; 3) dealing on own account; 4) portfolio management; 5) investment advice; 6) underwriting of financial instruments and or placing of financial instruments on a firm commitment basis; 7) placing of financial instruments without a firm commitment basis; 8) operation of Multilateral Trading Facilities.


Keywords: compliance, financial regulation, investment services

JEL Classifications: G20, G21, G24, G28

The Evolution of Compliance Function and Compliance Risk in Investment Services

SDA Bocconi research report 2009

This research focuses on the advancement of the Compliance function within banks, investment and insurance companies and on the effect of applying Community regulations as called for by the MiFID Directive. Eighty four financial intermediaries: banks, investment companies and insurance companies took part in this research. Two criteria have been used to interpret the results: 1) the prevailing workability within international and domestic intermediaries; 2) the intermediary typology, creating a distinction between banks, and of these cooperative banks, other financial intermediaries (investment companies) and insurance companies. The research continues what was carried out during 2007, where thirty five intermediaries, namely banks and investment companies were appraised. The present research broadens the spectrum to also include insurance companies. The data was collected using a questionnaire created and analysed by a group of researchers of the Research Division of SDA Bocconi School of Management. The collection phase of the data began in January 2009 and ended in March 2009. The research activity was carried out with the support of SIA SSB Group and in collaboration with AICOM (Associazione Italiana Compliance). With reference to the contents within this study is divided into four research areas: 1) positioning of the Compliance function within the organization; 2) the roles attributed to the Compliance function; 3) the methods used to measure, transfer and mitigate Compliance risk within investment services; 4) how the Compliance function interacts within and outside its structure. A fifth section is included in this report which focuses on the methodology of the research. The research is divided into three parts: I) the main progression steps of the Compliance function within financial intermediaries; II) how the MiFID compliant rules of the game have evolved in the investment services; III) the aim, the sample under investigation and the research methodology.

Keywords: Compliance, Financial services, Regulation, MIFID

JEL Classifications: G21, G22, G23, G28

An Asset Allocation Model Based on a Semi Variance Adjusted Sharpe Ratio

published in "Managerial Finance" 2006, co-authered with Riccardo Bramante

In asset allocation processes the estimation of standard deviations is often measured with error. As a result, the risk adjusted return ratios will be subject to estimation error. Since risk estimation is crucial in investment decisions, several risk measures have been suggested to take into consideration that risk changes through time. The choice of different risk measures can considerably change asset allocation decisions in the way in which assets are ranked on the basis of their risk-return profile. This paper is concerned with how to construct optimal portfolios that adapt quickly to changes in risk using a time varying asset allocation model based on a modified Sharpe Ratio measure.

Keywords: Asset allocation, semivariance, Sharpe ratio, portfolio optimization

JEL Classifications: C13, G11

Semi Variance and Semi Correlation for Financial Investments

published in "European Journal of Finance", 2005

Many studies show that international correlations have changed through time. This phenomenon changed many portfolio managers' practices, which are now strictly linked with sectors behaviours. In order to give reason for this management style, we provide some new evidences for correlation dynamics among geographic areas and business sectors. Nevertheless some researches offer theoretical basis for semi-variance optimisation, fewer authors analyse its contribution to financial portfolios. Here we apply the concept to compare whether it applies efficiently to sectors and countries. Conclusions are that: 1) short-term correlation, if adequately modelled, can be fundamental to im-plement a successful tactical asset allocation; 2) correlations lower volatile thanks to the application of semi-correlation measure;
3) computational methods applied to benchmark returns generate good results, especially in terms of direction, which is, in fact, the necessary input for the application of semi-correlation to the asset allocation process; 4) finally, gap ratios among returns and volatility grow for both the groups and extreme values of the frontiers and the upward of risk/return ratio is still better for geographical diversification, especially in the minimum values of expected returns.

Keywords: Correlation, asset allocation, sectors, benchmark, variance, optimization

JEL Classifications: C45, F3, G11, G15