Alessandro Trudda

2D Shape Classification Using Multifractional Brownian Motion

In this paper a novel approach to contour-based 2D shape recognition is proposed. The main idea is to characterize the contour of an object using the multifractional Brownian motion (mBm), a mathematical method able to capture the local self similarity and long-range dependence of a signal. The mBm estimation results in a sequence of Hurst coefficients, which we used to derive a fixed size feature vector. Preliminary experimental evaluations using simple classifiers with these feature vectors produce encouraging results, also in comparison with the state of the art.

Classifying Italian Pension Funds via GARCH Distance

The adoption of pension funds in the Italian social security policy has increased the offer of several investment funds. Workers have to decide what kind of investment to perform, the funds having a different composition and a subsequently different degree of risk. In this paper we propose the use of a distance between GARCH models as a measure of different structure of volatility of some funds, with the purpose of classifying a set of funds. Furthermore we extend the idea of equivalence between ARMA models to the GARCH case to verify the equality of the risk of each couple of funds. An application on thirteen Italian funds and fund indices is performed.

Financial Crisis: A New Measure for Risk of Pension Fund Portfolios.

It has been argued that pension funds should have limitations on their asset allocation, based on the risk profile of the different financial instruments available on the financial markets. This issue proves to be highly relevant at times of market crisis, when a regulation establishing limits to risk taking for pension funds could prevent defaults. In this paper we present a framework for evaluating the risk level of a single financial instrument or a portfolio. By assuming that the log asset returns can be described by a multifractional Brownian motion, we evaluate the risk using the time dependent Hurst parameter H(t) which models volatility. To provide a measure of the risk, we model the Hurst parameter with a random variable with mixture of beta distribution. We prove the efficacy of the methodology by implementing it on different risk level financial instruments and portfolios.

Financial and demographic risks impact on a pay-as-you-go pension fund

This paper studies the financial sustainability of a pay-as-you-go pension fund within a stochastic framework. To this aim, a set of risk indicators of the solvency of the fund are also constructed. Financial and demographic risks are analyzed by investigating and comparing their impact on the evolution of the fund. Numerical results are approached by means of a simulation methodology, on the Italian pension funds.