[show abstract][hide abstract] ABSTRACT: In this paper we propose a clustering procedure aimed at grouping time series with an association between extremely low values, measured by the lower tail dependence coefficient. Firstly, we estimate the coefficient using an Archimedean copula function. Then, we propose a dissimilarity measure based on tail dependence coefficients and a two-step procedure to be used with clustering algorithms which require that the objects we want to cluster have a geometric interpretation. We show how the results of the clustering applied to financial returns could be used to construct defensive portfolios reducing the effect of a simultaneous financial crisis.
Advances in Data Analysis and Classification 01/2011; 5:323-340. · 1.38 Impact Factor
[show abstract][hide abstract] ABSTRACT: The primary aim of the paper is to place current methodological discussions in macroeconometric modeling contrasting the ‘theory first’ versus the ‘data first’ perspectives in the context of a broader methodological framework with a view to constructively appraise them. In particular, the paper focuses on Colander’s argument in his paper “Economists, Incentives, Judgement, and the European CVAR Approach to Macroeconometrics” contrasting two different perspectives in Europe and the US that are currently dominating empirical macroeconometric modeling and delves deeper into their methodological/philosophical underpinnings. It is argued that the key to establishing a constructive dialogue between them is provided by a better understanding of the role of data in modern statistical inference, and how that relates to the centuries old issue of the realisticness of economic theories.
Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti", Econometrics Working Papers Archive. 01/2010;
[show abstract][hide abstract] ABSTRACT: In this paper some Archimedean copula functions for bivariate financial returns are studied. The choice of this family is due to their ability to capture the tail dependence, which is an association measure we can detect in many bivariate financial time-series. A time-varying version of these copulae is also investigated. Finally, the Value-at-Risk is computed and its performance is compared across different copula specifications.
Journal of Applied Statistics. 01/2009; 36(8):907-924.
[show abstract][hide abstract] ABSTRACT: The object of the paper is to compare of two approaches for the analysis of financial durations. The first is the parametric
approach (Autoregressive Conditional Duration model) implemented using the exponential, the Weibull, the Burr and the Pareto
density functions. The second makes use of bivariate and trivariate copula functions.
[show abstract][hide abstract] ABSTRACT: The instantaneous volatility of the price process is analyzed through the intraday financial durations between price changes. Previous research has traditionally dealt with parametric models without reaching a satisfactory level of adequacy. In this study, it is shown that by using a mixture of two exponential distributions a highly satisfactory fit can be obtained. The presence on financial markets of traders with different information sets makes reasonable the mixture assumption.
Studies in Nonlinear Dynamics & Econometrics. 02/2007; 8(2):1223-1223.
[show abstract][hide abstract] ABSTRACT: Refinements have been proposed for the autoregressive conditional duration model within the framework of financial durations. It is argued that a Pareto distribution is a meaningful representation for durations. The model is analyzed under the hypothesis of regime-switching parameters with different transition functions governed both by an observable and a latent variable.
[show abstract][hide abstract] ABSTRACT: Matching university places to students is not as clear cut or as straightforward as it ought to be. By investigating the matching algorithm used by the German central clearinghouse for university admissions in medicine and related subjects, we show that a procedure designed to give an advantage to students with excellent school grades actually harms them. The reason is that the three-step process employed by the clearinghouse is a complicated mechanism in which many students fail to grasp the strategic aspects involved. The mechanism is based on quotas and consists of three procedures that are administered sequentially, one for each quota. Using the complete data set of the central clearinghouse, we show that the matching can be improved for around 20% of the excellent students while making a relatively small percentage of all other students worse off.
Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti", Econometrics Working Papers Archive. 01/2006;
[show abstract][hide abstract] ABSTRACT: To evaluate and compare histogram features (mean lung attenuation, skewness, kurtosis) of low-dose and standard-dose CT in a group of patients affected by idiopathic interstitial pneumonitis.
We analyzed 16 patients affected by idiopathic interstitial pneumonitis. Spiral whole lung thin-section CT acquisition at standard dose (100 mAs) and three additional low-dose (50 mAs) CT images were obtained. After obtained frequency histograms, mean lung attenuation (MLA), skewness and kurtosis and three range of density (-700/-200 HU; -700/-400 HU; -500/-200 HU) of the standard-and low-dose thin-section CT scans were analyzed and compared.
The parameters obtained with low-dose and standard-dose spiral CT were correlated in a highly significant manner and were equivalent (p<0.01). The greatest correlation was found between standard-and low-dose kurtosis and standard and low-dose -700/-400 HU subrange of density (r=0.92; p<0.0001).
Our results prove that a quantitative CT objective evaluation in lung fibrosis can be successfully obtained with low-dose spiral CT, with reduced mA.
European Journal of Radiology 12/2005; 56(3):370-5. · 2.51 Impact Factor
[show abstract][hide abstract] ABSTRACT: To evaluate the percentage of cases in which emboli can be detected in unenhanced scans and to identify the cases in which they appear hyperattenuating or hypoattenuating in comparison to the circulating blood.
An angio-computed tomography (CT) scan was performed before and after contrast injection in 140 consecutive patients after clinical suspicion of pulmonary embolism. A radiologist analyzed the examination results thus obtained. The enhanced scan was analyzed first, and after detecting the thrombus, the unenhanced scan was evaluated.
Fifty-one examinations were positive for a pulmonary embolism; in 21 cases, it was possible to identify the embolus even in the unenhanced scans. In 10 cases, the clots were hyperattenuating in comparison to the circulating blood; in 5 cases, they were hypoattenuating; and in 6 cases, they were mixed hyper-hypoattenuating.
In a relatively high percentage of cases, particularly those of central thromboembolism, it is possible to identify and characterize the clots even in unenhanced scans.
[show abstract][hide abstract] ABSTRACT: Recently De Luca and Carfora (Statistica e Applicazioni 8:123–134, 2010) have proposed a novel model for binary time series, the Binomial Heterogenous Autoregressive (BHAR) model, successfully applied for the analysis of the quarterly binary time series of U.S. recessions. In this work we want to measure the efficacy of the out-of-sample forecasts of the BHAR model compared to the probit models by Kauppi and Saikkonen (Rev Econ Stat 90:777–791, 2008). Given the substantial indifference of the predictive accuracy between the BHAR and the probit models, a combination of forecasts using the method proposed by Bates and Granger (Oper Res Q 20:451–468, 1969) for probability forecasts is analyzed. We show how the forecasts obtained by the combination between the BHAR model and each of the probit models are superior compared to the forecasts obtained by each single model.
[show abstract][hide abstract] ABSTRACT: Financial market price formation and exchange activity can be investigated by means of ultra-high frequency data. In this article, we investigate an extension of the Autoregressive Conditional Duration (ACD) model of Engle and Russell (1998) by adopting a mixture of distribution approach with time-varying weights. Empirical estimation of the Mixture ACD model shows that the limitations of the standard base model and its inadequacy of modelling the behavior in the tail of the distribution are suitably solved by our model. When the weights are made dependent on some market activity data, the model lends itself to some structural interpretation related to price formation and information diffusion in the market.