Metodi statistici a variabili latenti per lo studio di fenomeni finanziari

Negli ultimi decenni il concetto di variabile latente ha riscosso un enorme successo nelle discipline statistiche come attestano i numerosi lavori scientifici presenti in letteratura. In particolare, nelle scienze sociali e in psicometria, l’uso del concetto di variabile latente è stato largamente adottato per far fronte al problema di misurare quantità che, in natura, non possono essere direttamente osservate. La vasta letteratura riguardante questa metodologia si espande, in maniera più limitata, anche al campo della ricerca economica ed econometrica. Nonostante esistano studi di modelli a struttura latente applicati a variabili di tipo economico, molto pochi sono i lavori che considerano variabili finanziarie e, finora, praticamente nessun ricercatore ha messo in connessione la teoria standard di portafoglio con la metodologia dei modelli statistici a variabili latenti. L’obiettivo del lavoro è quello di ricorrere alle potenzialità esplicative ed investigative dei metodi statistici a variabili latenti per l’analisi dei fenomeni finanziari. Si fa riferimento, in particolare, ai modelli a classe latente che consentono di sviluppare soluzioni metodologicamente corrette per importanti problemi ancora aperti in campo finanziario. In primo luogo, la natura stessa delle variabili finanziarie è riconducibile al paradigma delle variabili latenti. Infatti, variabili come il rischio ed il rendimento atteso non possono essere misurate direttamente e necessitano di approssimazioni per valutarne l’entità. Tuttavia, trascurare la natura non osservabile delle variabili finanziarie può portare a decisioni di investimento inopportune o, talvolta, addirittura disastrose. Secondariamente, vengono prese in considerazione le capacità dei modelli a classi latenti nel contesto della classificazione. Per i prodotti finanziari, infatti, una corretta classificazione sulla base del profilo (latente) di rischio e rendimento rappresenta il presupposto indispensabile per poter sviluppare efficaci strategie di investimento. Ci si propone, inoltre, di sviluppare un collegamento, finora mancante, tra uno dei principali riferimenti della finanza moderna, la teoria classica del portafoglio di Markowitz, e la metodologia statistica dei modelli a variabili latenti. In questo contesto, si vogliono investigare, in particolare, i benefici che i modelli a variabili latenti possono dare allo studio di ottimizzazione del profilo rischio - rendimento atteso di un portafoglio di attività finanziarie. Lo sviluppo di numeri indici dei prezzi delle attività finanziarie caratterizzati da una solida base metodologica rappresenta un ulteriore aspetto nel quale i modelli a classe latente possono svolgere un ruolo di fondamentale importanza. In particolare, si propone di analizzare il contesto dei numeri indici dei prezzi settoriali, che costituiscono uno dei riferimenti più importanti nelle strategie di diversificazione del rischio. Infine, il passaggio da una specificazione statica ad una analisi dinamica coglie aspetti metodologici di frontiera che possono essere investigati nell’ambito dei modelli markoviani a classi latenti. Il profilo latente di rischio – rendimento può essere, così, investigato in riferimento alle diverse fasi dei mercati finanziari, per le quali le probabilità di transizione consentono valutazioni di tipo previsivo di forte interesse.

Metodi avanzati di indagine di ammassi rocciosi a blocchi in matrice (bimrock).

The research focuses on the implementation and validation of advanced direct and indirect methods of investigation for the structural and mechanical characterisation of bimrocks. In particular, a non conventional in situ shear test has been develop in order to evaluate the strength parameters of bimrocks by properly taking into account the influence of blocks. Also, a geostatistical approach has been introduced for the investigation of block morphological and spatial properties from digital images, by means of a variographic analysis of the block Indicator Variable.

Applicazione di strumenti e metodi per la gestione ambientale di un territorio vasto - Sviluppo di un sistema di gestione ambientale in un ente pubblico secondo lo schema europeo EMAS e analisi di un sistema energetico territoriale

Environmental Management includes many components, among which we can include Environmental Management Systems (EMS), Environmental Reporting and Analysis, Environmental Information Systems and Environmental Communication. In this work two applications are presented: the developement and implementation of an Environmental Management System in local administrations, according to the European scheme "EMAS", and the analysis of a territorial energy system through scenario building and environmental sustainability assessment. Both applications are linked by the same objective, which is the quest for more scientifically sound elements; in fact, both EMS and energy planning are oftec carachterized by localism and poor comparability. Emergy synthesis, proposed by ecologist H.T. Odum and described in his book "Environmental Accounting: Emergy and Environmental Decision Making" (1996) has been chosen and applied as an environmental evaluation tool, in order complete the analysis with an assessment of the "global value" of goods and processes. In particular, eMergy syntesis has been applied in order to improve the evaluation of the significance of environmental aspects in an EMS, and in order to evaluate the environmental performance of three scenarios of future evolution of the energy system. Regarding EMS, in this work an application of an EMS together with the CLEAR methodology for environmental accounting is discussed, in order to improve the identification of the environmental aspects; data regarding environmental aspects and significant ones for 4 local authorities are also presented, together with a preliminary proposal for the integration of the assessment of the significance of environmental aspects with eMergy synthesis. Regarding the analysis of an energy system, in this work the carachterization of the current situation is presented together with the overall energy balance and the evaluation of the emissions of greenhouse gases; moreover, three scenarios of future evolution are described and discussed. The scenarios have been realized with the support of the LEAP software ("Long Term Energy Alternatives Planning System" by SEI - "Stockholm Environment Institute"). Finally, the eMergy synthesis of the current situation and of the three scenarios is shown.

Analysis of eruptive and seismic sequences to improve the short-and long-term eruption forecasting

Forecasting the time, location, nature, and scale of volcanic eruptions is one of the most urgent aspects of modern applied volcanology. The reliability of probabilistic forecasting procedures is strongly related to the reliability of the input information provided, implying objective criteria for interpreting the historical and monitoring data. For this reason both, detailed analysis of past data and more basic research into the processes of volcanism, are fundamental tasks of a continuous information-gain process; in this way the precursor events of eruptions can be better interpreted in terms of their physical meanings with correlated uncertainties. This should lead to better predictions of the nature of eruptive events. In this work we have studied different problems associated with the long- and short-term eruption forecasting assessment. First, we discuss different approaches for the analysis of the eruptive history of a volcano, most of them generally applied for long-term eruption forecasting purposes; furthermore, we present a model based on the characteristics of a Brownian passage-time process to describe recurrent eruptive activity, and apply it for long-term, time-dependent, eruption forecasting (Chapter 1). Conversely, in an effort to define further monitoring parameters as input data for short-term eruption forecasting in probabilistic models (as for example, the Bayesian Event Tree for eruption forecasting -BET_EF-), we analyze some characteristics of typical seismic activity recorded in active volcanoes; in particular, we use some methodologies that may be applied to analyze long-period (LP) events (Chapter 2) and volcano-tectonic (VT) seismic swarms (Chapter 3); our analysis in general are oriented toward the tracking of phenomena that can provide information about magmatic processes. Finally, we discuss some possible ways to integrate the results presented in Chapters 1 (for long-term EF), 2 and 3 (for short-term EF) in the BET_EF model (Chapter 4).

Comparazione di metodi per l'elaborazione di mappe di vulnerabilità degli acquiferi

Lo scopo di questa tesi di dottorato è la comparazione di metodi per redarre mappe della vulnerabilità degli acquiferi all’inquinamento. Sono state redatte le mappe di vulnerabilità dell’acquifero della conoide del Reno utilizzando i metodi parametrici SINTACS (Civita e De Maio, 1997) e DRASTIC (Aller et al., 1987). E' stato elaborato un modello tridimensionale del flusso tramite l'utilizzo del software di modellistica numerica FEFLOW. I risultati ottenuti sono stati confrontati con le mappe derivanti dall'appllicazione dei PCSM. E’ stato, inoltre, approfondito lo sviluppo di un modello inverso, che, partendo dalla distruzione del carico piezometrico, fornisce la distribuzione della conducibilità idraulica dell’acquifero.La conoscenza di questo parametro è, infatti, il punto di partenza per lo sviluppo di un nuovo metodo per la definizione della vulnerabilità basato sulla caratterizzazione dell'area di acquifero potenzialmente inquinabile rispetto ad uno sversamento in superficie di un inquinante.L’indice di vulnerabilità viene definito sulla lunghezza del cammino che un inquinante percorrere nell’arco di un anno.

Metodi Matematici per il Recupero dei Nessi Concettuali in Uno o più Testi: Entropia e Analisi della Semantica Latente.

Nella prima parte si analizza il metodo dell'entropia delle parole in un testo per recuperare quelle più rilevanti in base alla distribuzione delle stesse all'interno dell'opera. Nella seconda parte viene studiata l'analisi della semantica latente e le sue basi statistiche, algebriche e analitiche. Infine vengono effettuati degli esperimenti con l'utilizzo del software InfomapNLP sulla Divina Commedia.

Metodi di ottimizzazione morfologica nel progetto preliminare di propulsori aeronautici avanzati

The aim of this Doctoral Thesis is to develop a genetic algorithm based optimization methods to find the best conceptual design architecture of an aero-piston-engine, for given design specifications. Nowadays, the conceptual design of turbine airplanes starts with the aircraft specifications, then the most suited turbofan or turbo propeller for the specific application is chosen. In the aeronautical piston engines field, which has been dormant for several decades, as interest shifted towards turboaircraft, new materials with increased performance and properties have opened new possibilities for development. Moreover, the engine’s modularity given by the cylinder unit, makes it possible to design a specific engine for a given application. In many real engineering problems the amount of design variables may be very high, characterized by several non-linearities needed to describe the behaviour of the phenomena. In this case the objective function has many local extremes, but the designer is usually interested in the global one. The stochastic and the evolutionary optimization techniques, such as the genetic algorithms method, may offer reliable solutions to the design problems, within acceptable computational time. The optimization algorithm developed here can be employed in the first phase of the preliminary project of an aeronautical piston engine design. It’s a mono-objective genetic algorithm, which, starting from the given design specifications, finds the engine propulsive system configuration which possesses minimum mass while satisfying the geometrical, structural and performance constraints. The algorithm reads the project specifications as input data, namely the maximum values of crankshaft and propeller shaft speed and the maximal pressure value in the combustion chamber. The design variables bounds, that describe the solution domain from the geometrical point of view, are introduced too. In the Matlab® Optimization environment the objective function to be minimized is defined as the sum of the masses of the engine propulsive components. Each individual that is generated by the genetic algorithm is the assembly of the flywheel, the vibration damper and so many pistons, connecting rods, cranks, as the number of the cylinders. The fitness is evaluated for each individual of the population, then the rules of the genetic operators are applied, such as reproduction, mutation, selection, crossover. In the reproduction step the elitist method is applied, in order to save the fittest individuals from a contingent mutation and recombination disruption, making it undamaged survive until the next generation. Finally, as the best individual is found, the optimal dimensions values of the components are saved to an Excel® file, in order to build a CAD-automatic-3D-model for each component of the propulsive system, having a direct pre-visualization of the final product, still in the engine’s preliminary project design phase. With the purpose of showing the performance of the algorithm and validating this optimization method, an actual engine is taken, as a case study: it’s the 1900 JTD Fiat Avio, 4 cylinders, 4T, Diesel. Many verifications are made on the mechanical components of the engine, in order to test their feasibility and to decide their survival through generations. A system of inequalities is used to describe the non-linear relations between the design variables, and is used for components checking for static and dynamic loads configurations. The design variables geometrical boundaries are taken from actual engines data and similar design cases. Among the many simulations run for algorithm testing, twelve of them have been chosen as representative of the distribution of the individuals. Then, as an example, for each simulation, the corresponding 3D models of the crankshaft and the connecting rod, have been automatically built. In spite of morphological differences among the component the mass is almost the same. The results show a significant mass reduction (almost 20% for the crankshaft) in comparison to the original configuration, and an acceptable robustness of the method have been shown. The algorithm here developed is shown to be a valid method for an aeronautical-piston-engine preliminary project design optimization. In particular the procedure is able to analyze quite a wide range of design solutions, rejecting the ones that cannot fulfill the feasibility design specifications. This optimization algorithm could increase the aeronautical-piston-engine development, speeding up the production rate and joining modern computation performances and technological awareness to the long lasting traditional design experiences.

Towards Rapid Environmental Assessment and Coastal Forecasting in the Northern Adriatic Sea

A new Coastal Rapid Environmental Assessment (CREA) strategy has been developed and successfully applied to the Northern Adriatic Sea. CREA strategy exploits the recent advent of operational oceanography to establish a CREA system based on an operational regional forecasting system and coastal monitoring networks of opportunity. The methodology wishes to initialize a coastal high resolution model, nested within the regional forecasting system, blending the large scale parent model fields with the available coastal observations to generate the requisite field estimates. CREA modeling system consists of a high resolution, O(800m), Adriatic SHELF model (ASHELF) implemented into the Northern Adriatic basin and nested within the Adriatic Forecasting System (AFS) (Oddo et al. 2006). The observational system is composed by the coastal networks established in the framework of ADRICOSM (ADRiatic sea integrated COastal areaS and river basin Managment system) Pilot Project. An assimilation technique exerts a correction of the initial field provided by AFS on the basis of the available observations. The blending of the two data sets has been carried out through a multi-scale optimal interpolation technique developed by Mariano and Brown (1992). Two CREA weekly exercises have been conducted: the first, at the beginning of May (spring experiment); the second in middle August (summer experiment). The weeks have been chosen looking at the availability of all coastal observations in the initialization day and one week later to validate model results, verifying our predictive skills. ASHELF spin up time has been investigated too, through a dedicated experiment, in order to obtain the maximum forecast accuracy within a minimum time. Energetic evaluations show that for the Northern Adriatic Sea and for the forcing applied, a spin-up period of one week allows ASHELF to generate new circulation features enabled by the increased resolution and its total kinetic energy to establish a new dynamical balance. CREA results, evaluated by mean of standard statistics between ASHELF and coastal CTDs, show improvement deriving from the initialization technique and a good model performance in the coastal areas of the Northern Adriatic basin, characterized by a shallow and wide continental shelf subject to substantial freshwater influence from rivers. Results demonstrate the feasibility of our CREA strategy to support coastal zone management and wish an additional establishment of operational coastal monitoring activities to advance it.

Analysis and developments of uncertainty processors for real time flood forecasting

The hydrologic risk (and the hydro-geologic one, closely related to it) is, and has always been, a very relevant issue, due to the severe consequences that may be provoked by a flooding or by waters in general in terms of human and economic losses. Floods are natural phenomena, often catastrophic, and cannot be avoided, but their damages can be reduced if they are predicted sufficiently in advance. For this reason, the flood forecasting plays an essential role in the hydro-geological and hydrological risk prevention. Thanks to the development of sophisticated meteorological, hydrologic and hydraulic models, in recent decades the flood forecasting has made a significant progress, nonetheless, models are imperfect, which means that we are still left with a residual uncertainty on what will actually happen. In this thesis, this type of uncertainty is what will be discussed and analyzed. In operational problems, it is possible to affirm that the ultimate aim of forecasting systems is not to reproduce the river behavior, but this is only a means through which reducing the uncertainty associated to what will happen as a consequence of a precipitation event. In other words, the main objective is to assess whether or not preventive interventions should be adopted and which operational strategy may represent the best option. The main problem for a decision maker is to interpret model results and translate them into an effective intervention strategy. To make this possible, it is necessary to clearly define what is meant by uncertainty, since in the literature confusion is often made on this issue. Therefore, the first objective of this thesis is to clarify this concept, starting with a key question: should be the choice of the intervention strategy to adopt based on the evaluation of the model prediction based on its ability to represent the reality or on the evaluation of what actually will happen on the basis of the information given by the model forecast? Once the previous idea is made unambiguous, the other main concern of this work is to develope a tool that can provide an effective decision support, making possible doing objective and realistic risk evaluations. In particular, such tool should be able to provide an uncertainty assessment as accurate as possible. This means primarily three things: it must be able to correctly combine all the available deterministic forecasts, it must assess the probability distribution of the predicted quantity and it must quantify the flooding probability. Furthermore, given that the time to implement prevention strategies is often limited, the flooding probability will have to be linked to the time of occurrence. For this reason, it is necessary to quantify the flooding probability within a horizon time related to that required to implement the intervention strategy and it is also necessary to assess the probability of the flooding time.