Domenico Sartore

Relative benchmark rating and persistence analysis: Evidence from Italian equity funds

Abstract The recent introduction into the Italian mutual fund market of Morningstar performance rating of private institutions gives rise to the question of what is the relation between this relative benchmark measure and the other traditional performance measures. This paper provides a comprehensive analysis of the relative benchmark performance measure (Morningstar rating) applied to Italian equity funds. It is found that this performance measure is highly correlated with the classical performance measures (Sharpe ratio, Sortino ratio and Treynor ratio) and poorly correlated with the customized benchmark measure (Information ratio). Furthermore, performing a persistence analysis, using non-parametric methods Cross-product Ratio and Chi-squared test, it is observed that only the Morningstar rating measure generates a strong degree of persistence. These results deviate from most European studies, which argue that Italian mutual funds display weak persistence.

Developments of control theory for economic analysis

I: Introduction to Control Theory: Methods and Algorithms.- 1. Developments of Control Theory in Macroeconomics.- 2. Linear Controllability: Results and Open Questions.- 3. A System Theoretic Approach to the Theory of Economic Policy.- 4. Software for Economic Optimal Control Models.- II: Recent Developments of Control Theory: Objective Function Specification.- 5. Interactive Vector Optimization as a Complement to Optimal Control in Econometric Decision Models.- 6. Risk Reduction and the Robustness of Economic Policies.- 7. Optimal Economic Policies under a Crawling-Peg Exchange.- 8. Some Remarks on Forward Programming.- 9. Utility and Uncertainty in Intertemporal Choice.- 10. Gradient Methods for FIML Estimation of Econometric Models.- III: Recent Developments of Control Theory: A Game Theoretic Approach.- 11. Methods for the Simultaneous Use of Multiple Models in Optimal Policy Design.- 12. Optimal Policy Design in Interdependent Economies.- 13. Hierarchical Games for Macroeconomic Policy Analysis.- 14. A Dynamic and Stochastic Model of Price Leadership.- 15. Quality and Reputation Policies of Duopolists under Asymmetric Information.- IV: Economic and Econometric Analysis By Control Methods.- 16. A System Approach to Insurance Company Management.- 17. Capital Theoretics, Business Cycles and Feedback Policy: An Experiment in Macroeconomic Control.- 18. Exogeneity and Control.

US dollar/Euro exchange rate: a monthly econometric model for forecasting

The intent of this paper is the construction of an econometric model able to produce reliable and reasonable forecasts for the US dollar/Euro real exchange rate. In order to achieve this aim, an area-wide model is analysed. The aggregation is motivated by the fact that the Euro-zone is under a single monetary policy. Furthermore, a more parsimonious parametric model enables one to consider an important source of non-stationarity given by the presence of structural breaks using the multivariate cointegration analysis. Against the Meese-Rogoff critique, the out-of-sample one-step-ahead forecasts using actual values of the exogenous produced by the estimated VECM are reasonably satisfactory.

Square Root Iterative Filter: Theory and Applications to Econometric Models

This paper provides a new algorithm for estimating state space dynamic models and, as an example, it considers the estimation of time-varying parameter models. The novel elements of the algorithm are: a simple, easily implementable, square root method which is shown to solve the numerical problems affecting the standard Kalman filter algorithm and the related information filter and smoothing algorithms;an iterative framework, where information and covariance filters and smoothing are sequentially run in order to estimate all the parameters of the model; four different algorithms to consistently estimate the distribution of the estimated parameters, which are described and then compared by performing appropriate Montecarlo experiments.

Methodological Aspects of Time Series Back-Calculation

This paper provides the theoretical and operational framework for estimating past values of relevant time series starting from a (limited) information set. We consider a general approach that includes as special cases time series aggregation and temporal and/or spatial disaggregation problems. Furthermore, we explore the relevant problems and the possible solutions associated with a retropolation exercise, evidencing that linear models could be the preferred representation for the production of the needed data. The methodology is designed with a focus on economic time series but it could be considered even for other statistical areas. An empirical example is presented: we analyze the back-calculation of Eu15 Industrial Production Index comparing our approach with the Eurostat official one.

Combining forecasts: some results on exchange and interest rates

The aim of this work is to investigate whether the combination of forecasts plays an important role in the improvement of forecast accuracy Particular attention is paid to: (a) the methods of forecasting (the methods compared are neural networks, fuzzy logic, GARCH models, switching regime and chaotic dynamics); (b) combining the forecasts provided by the different methods. This work has also the aim of revising a short-term econometric forecast using a longer-term forecast. The revision process usually runs the opposite way (revision is made on a longer-term forecast using a short-term one to reflect the current available information, but it is not excluded that it is possible to proceed as described above. Daily data from the financial market is used. Some empirical applications on exchange and interest rates are given.

A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets

This article develops a new Markov-switching vector autoregressive (VAR) model with stochastic correlation for contagion analysis on financial markets. The correlation and the log-volatility dynamics are driven by two independent Markov chains, thus allowing for different effects such as volatility spill-overs and correlation shifts with various degrees of intensity. We outline a suitable Bayesian inference procedure based on Markov chain Monte Carlo algorithms. We then apply the model to some major and Asian-Pacific cross rates against the U.S. dollar and find strong evidence supporting the existence of contagion effects and correlation drops during crises, closely in line with the stylized facts outlined in the contagion literature. A comparison of this model with its closest competitors, such as a time-varying parameter VAR, reveals that our model has a better predictive ability. Supplementary materials for this article are available online

Bayesian Markov Switching Stochastic Correlation Models

This paper builds on Asai and McAleer (2009) and develops a new multivariate Dynamic Conditional Correlation (DCC) model where the parameters of the correlation dynamics and those of the log-volatility process are driven by two latent Markov chains. We outline a suitable Bayesian inference procedure, based on sequential MCMC estimation algorithms, and discuss some preliminary results on simulated data. We then apply the model to three major cross rates against the US Dollar (Euro, Yen, Pound), using high-frequency data since the beginning of the European Monetary Union. Estimated volatility paths reveal significant increases since mid-2007, documenting the destabilizing effects of the US sub-prime crisis and of the European sovereign debt crisis. Moreover, we find strong evidence supporting the existence of a time-varying correlation structure. Correlation paths display frequent shifts along the whole sample, both in low and in high volatility phases, pointing out the existence of contagion effects closely in line with the mechanisms outlined in the recent contagion literature (Forbes and Rigobon (2002) and Corsetti at al. (2005)).

Risk Aversion: Differential Conditions for the Concavity in Transformed Two-Parameter Distributions

The condition of Risk Aversion implies that the Utility Function must be concave. We take into account the dependence of the Utility Function on the return that has any type of two-parameter distribution; it is possible to define Risk and Target, that usually is the Expected value of the return, as a generic function of these two parameters. This paper determines the Differential Conditions for the definitions of Risk and Target that maintain the Concavity of the Expected Utility Function downward in the 3D space of the Risk, Target and Expected Utility Function. As a particular case, in the paper we discuss these conditions in the case of the CRRA Utility Function and the Truncated Normal distribution. Furthermore, different measures of Risk are chosen, as Value at Risk (VaR) and Expected Shortfall (ES), to verify if these measures maintain the downward concavity property for the Expected Utility Function.

Sovereign Risk and Contagion Effects in the Eurozone: A Bayesian Stochastic Correlation Model

This research proposes a Bayesian multivariate stochastic volatility (MSV) model to analyze the dynamics of sovereign risk in eurozone CDS markets during the recent financial crisis. We follow an MCMC approach to parameters and latent variable estimation and provide evidence of significant volatility shifts in asset returns, strong simultaneous increases in cross-market correlations, as well as sharp declines in correlations patterns. Overall, these findings are highly consistent with various empirical characterizations of contagion put forward in the literature, allowing us to conclude that the recent financial crisis generated severe contagion effects in sovereign debt markets of eurozone countries.