Combination of multivariate volatility forecasts

This paper proposes a novel approach to the combination of conditional covariance matrix forecasts based on the use of the Generalized Method of Moments (GMM). It is shown how the procedure can be generalized to deal with large dimensional systems by means of a two-step strategy. The finite sample properties of the GMM estimator of the combination weights are investigated by Monte Carlo simulations. Finally, in order to give an appraisal of the economic implications of the combined volatility predictor, the results of an application to tactical asset allocation are presented.Multivariate GARCH, Forecast Combination, GMM, Portfolio Optimization

On nonlocally interacting metrics, and a simple proposal for cosmic acceleration

We propose a simple, nonlocal modification to general relativity (GR) on large scales, which provides a model of late-time cosmic acceleration in the absence of the cosmological constant and with the same number of free parameters as in standard cosmology. The model is motivated by adding to the gravity sector an extra spin-2 field interacting nonlocally with the physical metric coupled to matter. The form of the nonlocal interaction is inspired by the simplest form of the Deser-Woodard (DW) model, $\alpha R\frac{1}{\Box}R$, with one of the Ricci scalars being replaced by a constant $m^{2}$, and gravity is therefore modified in the infrared by adding a simple term of the form $m^2\frac{1}{\Box}R$ to the Einstein-Hilbert term. We study cosmic expansion histories, and demonstrate that the new model can provide background expansions consistent with observations if $m$ is of the order of the Hubble expansion rate today, in contrast to the simple DW model with no viable cosmology. The model is best fit by $w_0\sim-1.075$ and $w_a\sim0.045$. We also compare the cosmology of the model to that of Maggiore and Mancarella (MM), $m^2R\frac{1}{\Box^2}R$, and demonstrate that the viable cosmic histories follow the standard-model evolution more closely compared to the MM model. We further demonstrate that the proposed model possesses the same number of physical degrees of freedom as in GR. Finally, we discuss the appearance of ghosts in the local formulation of the model, and argue that they are unphysical and harmless to the theory, keeping the physical degrees of freedom healthy.Comment: 47 pages in JCAP style, 7 figures. Some discussions extended in response to referee's comments. Version accepted for publication in JCA

The Usage of Credit Cards: An Empirical Analysis on Italian Households Panel Data

Credit cards, both as mean of payment and borrowing, rise many economic issues. The credit card services can be viewed as a two-sided network platform affected by indirect network externalities. The distribution of prices faced by the two sides influences market participation and the overall volume of demand. Consumers may hold or use credit cards from multiple networks leads to a ‘multi-homing’ effect that is of great importance in determining the outcome of the industry. Moreover, some studies show that the multiple credit cards can be seen as a device to access to more financing, making family bankruptcy more likely. In this paper we model the number of credit cards held by a panel of Italian household over the period 1991-2010 using demographic, socio-economic and geographical variables as potential predictors and panel data techniques for count data. The reached results can be of interest for implementing market strategies in credit card industry and, in particular, to investigate peculiar effect such as “multihoming” and “co-holding”. Keywords: Credit cards, Panel data, Count-data model

Corporate Governance, Investment, Profitability and Insolvency Risk: Evidence from Italy

The research aims to study the structural and functional characteristics of food and beverage companies, focusing on corporate governance, investment and financing decisions, innovation, profitability, and risk of insolvency. The analysis is based on a mixed type investigation method carried out on a random stratified sample of 274 firms. The empirical findings reveal that a large prevalence of companies is owned by a single person or by a limited number of partners (often of the same family). Owners and their families centralize decision-making power. The prevalence of companies made investment in innovation. The investments are mainly financed (78%) by the self-financing or by shareholders' capital. The investigation of the causal relationships that link corporate risk, profitability, and the propensity to invest and innovate with the other explanatory variables of business management highlighted further significant aspects

Governance, Innovation, Profitability, and Credit Risk: Evidence from Italian manufacturing firms

The research focuses attention on companies in the chemical-plastic sector, investigating corporate governance, investment and financing decisions, innovation, profitability, and credit risk. The investigation method used is mixed. The data and information were extracted from official databases and from a structured questionnaire. The stratified random method was used for sampling. 178 firms are included in the sample. The results show a prevalence of companies owned by a single person or a limited number of shareholders (in some cases of the same family), where the owners centralize decision-making power. Companies have a strong propensity to invest in innovation. Investments are mainly financed by self-financing or equity capital. The analysis of the causal relationships highlights further significant aspects relating to credit risk, profitability and innovation

Concepts and tools for nonlinear time series modelling

Tools and approaches are provided for nonlinear time series modelling in econometrics. A wide range of topics is covered, including probabilistic properties, statistical inference and computational methods. The focus is on the applications but the ideas of the mathematical arguments are also provided. Techniques and concepts are illustrated by various examples, Monte Carlo experiments and a real application

Concepts and tools for nonlinear time series modelling

Tools and approaches are provided for nonlinear time series modelling in econometrics. A wide range of topics is covered, including probabilistic properties, statistical inference and computational methods. The focus is on the applications but the ideas of the mathematical arguments are also provided. Techniques and concepts are illustrated by various examples, Monte Carlo experiments and a real application

Authentication of Sorrento walnuts by NIR spectroscopy coupled with different chemometric classification strategie

Walnuts have been widely investigated because of their chemical composition, which is particularly rich in unsaturated fatty acids, responsible for different benefits in the human body. Some of these fruits, depending on the harvesting area, are considered a high value-added food, thus resulting in a higher selling price. In Italy, walnuts are harvested throughout the national territory, but the fruits produced in the Sorrento area (South Italy) are commercially valuable for their peculiar organoleptic characteristics. The aim of the present study is to develop a non-destructive and shelf-life compatible method, capable of discriminating common walnuts from those harvested in Sorrento (a town in Southern Italy), considered a high quality product. Two-hundred-and-twenty-seven walnuts (105 from Sorrento and 132 grown in other areas) were analyzed by near-infrared spectroscopy (both whole or shelled), and classified by Partial Least Squares-Discriminant Analysis (PLS-DA). Eventually, two multi-block approaches have been exploited in order to combine the spectral information collected on the shell and on the kernel. One of these latter strategies provided the best results (98.3% of correct classification rate in external validation, corresponding to 1 misclassified object over 60). The present study suggests the proposed strategy is a suitable solution for the discrimination of Sorrento walnuts. © 2020 by the authors

Self-assessment and career choices: an on-line resource for the university of Salerno

Aim of this paper is to examine the different factors that might influence high school students in their choice of a University degree program and the relationship with occupational interests. In this framework, an on-line questionnaire, “The Self-Assessment and Career Choices scale”, has been proposed for the University of Salerno as a service offered by the orientation office in order to investigate the career decision process. In the following, a brief description of the scale is given, along with the main results of the exploratory analysis performed on the data collected during the first year of implementation of the scale on the web