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Modeling non-stationarities in high-frequency financial time series
No full textWe study tick-by-tick financial returns for the FTSE MIB index of the Italian Stock Exchange (Borsa Italiana). We confirm previously detected non-stationarities. Scaling properties reported before for other high-frequency financial data are only approximately valid. As a consequence of our empirical analyses, we propose a simple model for non-stationary returns, based on a non-homogeneous normal compound Poisson process. It turns out that our model can approximately reproduce several stylized facts of high-frequency financial time series. Moreover, using Monte Carlo simulations, we analyze order selection for this class of models using three information criteria: Akaike's information criterion (AIC), the Bayesian information criterion (BIC) and the Hannan–Quinn information criterion (HQ). For comparison, we perform a similar Monte Carlo experiment for the ACD (autoregressive conditional duration) model. Our results show that the information criteria work best for small parameter numbers for the compound Poisson type models, whereas for the ACD model the model selection procedure does not work well in certain cases
Accordi preventivi e prospettive evolutive della cooperazione tra fisco e imprese
No full textGli accordi preventivi delineano un modulo procedurale molto efficace, ancorché impegnativo da percorrere, per affrontare questioni di elevata complessità, specie quando le difficoltà ricostruttive che prospettano investono tanto profili di diritto quanto, e in particolare, profili di fatto. Il loro punto di forza è la cooperazione tra Ufficio e impresa istante, una cooperazione che la relativa disciplina, non solo postula, ma persino impone, sia nella fase istruttoria, sia in quella attuativa. L’efficacia del modulo considerato spinge a interrogarsi sulla possibilità di ampliarne la sfera di applicazione, allo stato circoscritta a questioni qualificate da profili di internazionalità
Proceedings of the International neural networks society
No full textCapabilities and, in particular, Innovation Capability (IC), are fundamental strategic assets for companies in providing and sustaining their competitive advantage. IC is the firms' ability to mobilize and create new knowledge applying appropriate process technologies and it has been investigated by means of its main determinants, usually divided into internal and external factors. In this paper, starting from the patent data, the patent's forward citations are used as proxy of IC and the main patents' features are considered as proxy of the determinants. In details, the main purpose of the paper is to understand the patent's features that are relevant to predict IC. Three different algorithms of machine learning, i.e., Least Squares (RLS), Deep Neural Networks (DNN), and Decision Trees (DT), are employed for this investigation. Results show that the most important patent's features useful to predict IC refer to the specific technological areas, the backward citations, the technological domains and the family size. These findings are confirmed by all the three algorithms used.16-18 April 201
Interesse sociale vs. interesse "sociale" nei modelli organizzativi di gruppo presupposti dal d.lgs. n. 254/2016
No full text
Budgetary rigour with stimulus in lean times: policy advices from an agent-based model
No full textThe 2008 financial crisis, and the subsequent global recession, triggered a wide-spread economic and political debate on the proper policy combination to deal with the crisis and to prevent similar ones in the future. Probably, the main dispute has been around the use of fiscal instruments in order to foster growth while keeping public debt under control. The European Union, for instance, endorsed “austerity” measures for fiscal consolidation but has been sharply criticized by several scholars. This paper aims at contributing to the current debate by presenting the outcomes of a computational study performed with the Eurace agent-based model. We set up an experiment with two base policy scenarios, i.e., stability and growth pact and fiscal compact, incrementally enriching them with complementary policies which relax fiscal rigidity and introduce quantitative easing. Results show that budgetary rigour performs well if and only if some mechanisms of fiscal relaxation and monetary accommodation are considered during bad times; thus confirming in a richer and more realistic model setting the fundamental tenet of Keynesian economics about the importance of sustaining aggregate demand during recessions
Dissimilarity measure for ranking data via copula
No full textA new distance measure is defined for ranking data by using copula functions. This distance evaluates the dissimilarity between subjects expressing their preferences by rankings in order to segment them by hierarchical cluster analysis. The proposed distance builds upon the Spearmans grade correlation coefficient on a transformation of the ranks denoting the levels of the importance assigned by subjects under classification to k objects. The copula is a flexible way to model different types of dependence structures in the data and to consider different situations in the classification process. For example, by using copulae with lower and upper tail dependence, we emphasize the agreement on extreme ranks, when they are considered more important.14-16 December 201