Annali del Dipartimento di metodi e modelli per l'economia, il territorio e la finanza

Dynamic optimal asset allocation in a multivariate setting

2024-04-03T11:22:42+00:00

This article analyzes a portfolio allocation problem to determine how resources should be allocated among several possible investments. Investors aim to maximize the profit of an investment while also considering the risks arising from infrequent events. The global financial crisis, which began with subprime mortgages in the United States, has fundamentally changed the way we invest. As we know, investors want to maximize returns while controlling the risk associated with a particular investment. This behavior must be modeled mathematically using optimal control theory and expected utility maximization. A continuous-time market is considered in a multivariate context in which there exist risky asset classes and a risk-free asset with a constant interest rate. We deviate from the traditional approach by considering co-precision, the inverse of the covariance matrix, as a measure of risk. The optimal weights obtained are proportional (inversely) to the risk measure (volatility). The model is tested on 11 asset classes used by a large company also carrying out a stress test on the jump component to analyze the allocation of the investors’ portfolio in a real context.

CDO su misura: la nuova era delle cartolarizzazioni

2024-04-30T09:52:38+00:00

This paper reviews the structure of Collateralized Debt Obligations (CDOs), finan cial products used in the period of the 2008 sub-prime mortgage crisis, in order to understand the reasons that lead them to be considered the main responsible for it. The legacy of CDOs, which is reflected in Bespoke Tranche Opportunities (BTOs), is then discussed in order to understand whether they are equally ”toxic” products, as CDOs were defined after the outbreak of the crisis, or they are really innovative tool of securitization.

Location models of electric charging stations in the city of Rome

2024-05-02T13:41:46+00:00

The issue of the location of charging stations for electric vehicles is becoming very important due to governmental decisions on electric mobility. Many authors have addressed this problem with the support of graph theory and graph optimization. In dealing with this problem, typical operational research models and approaches used for facility location, such as p-median, coverage problem and queuing theory, have been resorted to. In this paper we apply these models to the location of charging stations in the city of Rome. In particular, we analyze the suitability of existing charging sites and suggest where to implement new chargers using a p-median-like model. Finally, we study the waiting time distribution when the nearest charging stations are occupied, and we use queuing theory to show how much demand for the service would improve with the implementation of the new charging points.