SEMIPARAMETRIC VECTOR MEM

Financial time series are often non‐negative‐valued (volumes, trades, durations, realized volatility, daily range) and exhibit clustering. When joint dynamics is of interest, the vector multiplicative error model (vMEM; the element‐by‐element product of a vector of conditionally autoregressive scale factors and a multivariate i.i.d. innovation process) is a suitable strategy. Its parameters can be estimated by generalized method of moments, bypassing the problem of specifying a multivariate distribution for the errors. Simulated results show the gains in efficiency relative to an equation‐by‐equation approach. A vMEM on several measures of volatility justifies a joint approach revealing full interdependence. Copyright © 2012 John Wiley & Sons, Ltd.     

Shrinkage estimation of semiparametric multiplicative error models

Within models for nonnegative time series, it is common to encounter deterministic components (trends, seasonalities) which can be specified in a flexible form. This work proposes the use of shrinkage type estimation for the parameters of such components. The amount of smoothing to be imposed on the estimates can be chosen using different methodologies: Cross-Validation for dependent data or the recently proposed Focused Information Criterion. We illustrate such a methodology using a semiparametric autoregressive conditional duration model that decomposes the conditional expectations of durations into their dynamic (parametric) and diurnal (flexible) components. We use a shrinkage estimator that jointly estimates the parameters of the two components and controls the smoothness of the estimated flexible component. The results show that, from the forecasting perspective, an appropriate shrinkage strategy can significantly improve on the baseline maximum likelihood estimation.     

Buy Local! Familiarity and Preferences for Extra Virgin Olive Oil of Italian Consumers

Over the last few years, the origin of the local product has played a central role in consumer choices. This study explores what Italian consumers want and look for when purchasing olive oil by combining a web-based survey and a perceived analysis technique. In particular, preferences for different olive oil attributes as well as the psychographic traits of respondents were revealed through a web-based questionnaire administered to Italian consumers (N = 179). From this questionnaire, respondents who indicated their availability to participate further underwent a preference test under blind conditions (N = 99). Respondents also did an expectation test based on the visual observation of the labels. Results showed that the majority of consumers considered local production, PDO and region as factors of highest importance in determining olive oil quality.     

A virtual voyage through 3D structures generated by chaotic mixing of magmas and numerical simulations: a new approach for understanding spatial and temporal complexity of magma dynamics

In this contribution, we present a virtual voyage through 3D structures generated by chaotic mixing of magmas and numerical simulations with the aim to highlight the power of 3D representations in the understanding of this geological phenomenon. In particular, samples of mixed juveniles from Salina island (Southern Italy) are reconstructed in 3D by serial lapping and digital montage and numerical simulations are performed by using a 3D chaotic dynamical system. Natural and simulated magma mixing structures are visualized by using several multimedia tools including animations and “virtual reality” models. It is shown that magma interaction processes can generate large spatial and temporal compositional heterogeneities in magmatic systems. The same topological structures are observed in both 3D reconstructed rock samples and chaotic numerical simulations, indicating that the mixing of magmas is governed by chaotic dynamics. The use of 3D multimedia models gives the opportunity to penetrate into magma mixing structures and to understand their significance in the context of magma dynamics. Such an approach is very powerful since multimedia tools can strongly capture the attention of the reader bringing him/her into an interactive and memorable geological experience.     

Modelling the spatiotemporal distribution of the incidence of resident foreign population

Many European countries have recently experienced a substantial increase in the proportion of immigrants in their populations. The incidence of resident foreigners calculated at a national level does not provide information on the local spatial and temporal distribution of the phenomenon. This information may be of crucial importance for planning local policies. In this article, we suggest a tool for practitioners to provide spatiotemporal maps representing the local distribution of the incidence of resident foreigners in the territory, and changes in spatial trends over time. We illustrate this with Italian data at a municipal level, for the period 2003–2008. To account for spatiotemporal interactions in the data, we propose using a generalized additive model incorporating a smoother of the time and space dimensions. Specifically, we set up a tensor product smoother combining a cubic regression spline basis for time and a soap film spline basis for space. This approach provides a consistent framework to produce spatiotemporal maps which could be effectively used by policy makers to decide the allocation of economic resources at a local level.     

Manipulation of profits in Italian publicly-funded healthcare trusts

ABSTRACT

This paper examines earnings management in state-funded Italian healthcare trusts. Italy is unique in requiring trusts to have balanced budgets by law. Small negative and positive deviations from a balanced budget had quite different consequences. The authors found no evidence of accounting manipulation when trusts posted small losses. However, trusts were found to manipulate discretionary accruals, provisions and non-operating expenses to reduce small positive deviations from zero-profit.     

Internet Multiattribute Group Decision Support in Electronic Commerce

The rapid growth of the Internet has provided the means for distributed organizational decision making for electronic commerce. Members of organizations can jointly investigate products, exchange information, and make decisions on-line from remote sites. Internet-based multiattribute group decision making is characterized by three aspects, (i) individual interactive decision making, (ii) communication means, and (iii) group consensus reaching. The purpose of this research was to study the role of communication and individual decision strategies and their influence on multiattribute group decision making and consensus reaching in organizational electronic commerce settings. The results of this study indicate that analytic decision support is indispensable in collaborative Internet-based decision making, that a perfect match of analytic decision support and communication channels must be achieved, and that efficiency of individual decision support should be compromised for higher confidence in the group's decisions. The results of this study also confirm findings by Häubl and Trifts (2000) that interactive decision analytic support has positive effects on the quality and efficiency of individual decision making, and findings by Limayem and DeSanctis (2000) and Todd and Benbesat (2000), that decision makers will use normative decision models if they require little effort and if decisional guidance is provided. The conclusion drawn from this study is that the continuously evolving Internet technology for collaborative decision making is only one aspect for better organizational decision making – the crucial aspect, however, will be the development and optimal integration of analytic decision models, communication channels, and consensus reaching mechanisms.     

The effects of trading activity on market volatility

The paper re-examines the question of excessive implied persistence of volatility estimates when GARCH type models are used. Ten actively traded US stocks are considered and as already established in the literature, when volume traded is inserted in the GARCH (1, 1) or (EGARCH 1, 1) models for returns, the estimated persistence is decreased. Since volume is affected also by within-the-day price movements and hence is not weakly exogenous relative to returns, alternative proxies for trading activities are suggested. It is concluded that the difference between the opening price and the closing price of the previous day accounts also for most of the persistence in the autoregressive conditional heteroskedasticity.