wp2009_01 (Econometrics, Statistics)
Intra-daily Volume Modeling and Prediction for Algorithmic Trading
Christian T. Brownlees, Fabrizio Cipollini, Giampiero M. Gallo
The explosion of algorithmic trading has been one the most recent innovations in the financial industry. Many of this algorithms consist of automated trading strategies that attempt to minimize transaction costs by optimally placing transactions orders. The key ingredient of many of these strategies are intra-daily volume forecasts. This work proposes a dynamic model for intra–daily volume forecasting that captures salient features of the series such a intra-daily periodicity and volume asymmetry. Results show that the proposed methodology is able to significantly outperform some of the common volume forecasting methods.
Published as Journal of Financial Econometrics, Volume 9, Issue 3, pp. 489-518, 2011; link, published.
wp2009_02 (Econometrics, Statistics)
Automated Variable Selection in Vector Multiplicative Error Models
Fabrizio Cipollini, Giampiero M. Gallo
Multiplicative Error Models (MEM) can be used to trace the dynamics of non–negative valued processes. Interactions between several such processes are accommodated by the vector MEM and estimated by maximum likelihood (Gamma marginals with copula functions) or by Generalized Method of Moments. In choosing the relevant variables one can follow an automated procedure where the full specification is successively pruned in a general–to–specific approach. An efficient and fast algorithm is presented in this paper and evaluated by means of a simulation and a real world example of volatility spillovers in European markets.
Published as Computational Statistics and Data Analysis, Volume 54, Issue 11, pp. 2470-2486 , 2009; link, published.
wp2009_03 (Econometrics, Statistics)
Semiparametric vector MEM
Fabrizio Cipollini, Robert F. Engle, Giampiero M. Gallo
In financial time series analysis we encounter several instances of non–negative valued processes (volumes, trades, durations, realized volatility, daily range, and so on) which exhibit clustering and can be modeled as the product of a vector of conditionally autoregressive scale factors and a multivariate iid innovation process (vector Multiplicative Error Model). Two novel points are introduced in this paper relative to previous suggestions: a more general specification which sets this vector MEM apart from an equation by equation specification; and the adoption of a GMM-based approach which bypasses the complicated issue of specifying a general multivariate non–negative valued innovation process. A vMEM for volumes, number of trades and realized volatility reveals empirical support for a dynamically interdependent pattern of relationships among the variables on a number of NYSE stocks.
Published as Journal of Applied Econometrics (early view), Volume -, Issue -, pp. -, 2012; link, published.
Exploiting Nonlinear Difference-in-Difference Assumptions in a Regression Discontinuity Design
Fabrizia Mealli, Carla Rampichini
The paper tackles the problem of identification of treatment effects in a regression-discontinuity-design (RDD) in the presence of heterogeneous effects. A RDD allows identification of average treatment effects only for a subset of individuals around the threshold for the participation status. We consider a set-up where a budget-constraint induced threshold splits the relevant population into two groups, the ex-post eligible and ineligible individuals, and application in both groups is determined according to rules potentially unknown to the researcher, so application (or participation) is not mandatory but voluntary. We show how this sharp RDD design allows to test some assumptions and extend results away from the threshold by exploiting DID hypotheses. The proposed tools are applied to the evaluation of Italian university grants.
wp2009_05 (Statistics, Econometrics)
Evaluating the effect of training on wages in the presence of noncompliance and missing outcome data
Paolo Frumento, Fabrizia Mealli, Barbara Pacini, Donald B. Rubin
Here, the effects of a training program on employment and wages are evaluated, using data from a randomized study, the National Job Corps Study, and the principal stratification approach to simultaneously address the complications of noncompliance, truncation of wages by nonemployment, and missing outcomes. We conduct a likelihood-based analysis, proposing different ways of improving computational efficiency and identifiability using the theory of finite mixture models and exploiting the EM algorithm. We maintain an IV exclusion restriction assumption on the outcomes, while monotonicity of compliance holds by design. We provide estimates with and without assuming monotonicity of the truncation of wages, under the Missing at Random assumption of outcome missingness. For compliers, results show that the effect on employment is generally positive; however, there is a subgroup of complying participants for whom the program is detrimental on employment in the short term, although this effect becomes negligible in the long term. For the subgroup of always-employed compliers, that is, those who would be employed whether trained or not, the effect of the training on wages is positive, both in the short and long term. According to our estimates, participation in the Job Corps training program is found to be effective: 208 weeks after participation, we found a positive causal effect on employment of about 5 %, with an average causal effect on wages for the always employed of about 0.3$/hour.
Measurement error in multilevel models with sample cluster means
Leonardo Grilli, Carla Rampichini
The paper explores some issues related to endogeneity in multilevel models, focusing on the case where the random effects are correlated with a level 1 covariate in a linear random intercept model. We consider two basic specifications, without and with the sample cluster mean. It is generally acknowledged that the omission of the cluster mean may cause omitted-variable bias. However, it is often neglected that the inclusion of the sample cluster mean in place of the population cluster mean entails a measurement error that yields biased estimators for both the slopes and the variance components. In particular, the contextual effect is attenuated, while the residual level 2 variance is inflated. After outlining a suitable framework, we derive explicit formulae for measurement error biases that allow to implement simple corrections. The theoretical analysis is supplemented with a simulation study and a discussion of the implications for effectiveness evaluation.
L’eterogeneità demografica dei paesi in via di sviluppo tra realtà e mito della convergenza
Aurora Angeli, Silvana Salvini
The aim of this work is to analyze jointly the trend of both demographic and socio-economic indicators that characterize population living in countries with a low and a medium level of Human Development Index (HDI). We intend to outline differences and similarities according to fertility and mortality levels and evolution together with the trend in education, maternal and child health, women status and (when available) economic inequality. A preliminary analysis of some indicators confirms the persistence of variability among countries across regional and HDI groups.
Strategie lavorative e intenzioni riproduttive di uomini e donne in coppia: uno sguardo alla situazione italiana
Silvana Salvini, Sara Pasqual, Daniele Vignoli
The purpose of this study is to analyze the link between reproductive intentions of men and women in couple and their employment situation. The data used stems from the 2003 Istat Multipurpose Household Survey on "Family and Social Subjects" – which also constitutes the Italian variant of the Gender and Generation Survey. The exploratory analysis has shown that a combination of demographic, cultural and economic factors are influencing the reproductive intentions of the Italians. In addition, our analysis suggests the important role played by the perception of the future prospects of the actual job in determining reproductive intentions. The plan to have a(nother) child seems to be highly dependent on one’s actual financial situation, in a context where the general perception of economic insecurity is becoming more and more widespread. Furthermore, we found that, when the re-conciliation of the roles of mother and worker is facilitated by a collaborative partner, also fertility intentions are higher.
wp2009_09 (Economic Statistics, Statistics)
Un'analisi CGE dell'impatto del turismo sul sistema economico della Sardegna
Guido Ferrari, Tiziana Laureti, Luca Secondi
L’impatto del turismo sui sistemi economici è un tema che da diversi anni interessa ricercatori, analisti economici e policy makers, sia pubblici che privati. La multisettorialità che caratterizza l’attività turistica gioca, infatti, un ruolo fondamentale sia nelle economie nazionali sia, e a maggior ragione, in quelle regionali per attivare, potenziare e stimolare la quasi totalità dei settori. Una corretta valutazione dell’incidenza dell’attività turistica necessita di strumenti metodologici che consentano una completa ed estesa identificazione della molteplicità di interrelazioni esistenti all’interno di un sistema economico. Il nostro lavoro, attraverso la computazione di un modello CGE regionale, si pone l’obiettivo di fornire un quadro di sintesi del sistema economico della regione Sardegna e dell’importante ruolo che in esso riveste l’attività turistica. In particolare, l’introduzione di tre diversi scenari di detassazione fiscale ci consente di verificare e valutare, da un lato, gli effetti che le manovre di politica economica ipotizzate producono sull’attività turistica stessa e sui principali aggregati macro-economici e dall’altro, i legami esistenti tra il turismo e le principali branche di rilievo del sistema economico regionale.
wp2009_10 (Social Statistics)
Social Exclusion in European Regions: a Multilevel Latent Class Approach
In recent years there has been a shift in public discourses of several European countries from “poverty” to “social exclusion”, a terminology emerged with reference to problems related to a new poverty that is not just monetary. The current European debate has revitalized the path towards Lisbon 2010, making social inclusion a key ele-ment of socio-economic development. After giving an operational definition of “social exclusion” referring to different areas of human life, in this contribution we propose a hierarchical Latent Class (LC) model for the analysis of the differences and the similarities about experiences and per-ceptions of social exclusion in European regions. Social exclusion is a situation that affects individuals, and derives from a multidimensional deprivation in different domains of their life, namely an economic, a social and an institutional dimension. We treat social exclusion as a latent construct, quantified via indirect manifest indicators referring to the identified dimensions. The latent classes represent the latent levels of social exclusion, which structure the individuals with re-spect to a set of observed indicators. The regional differences in the latent variable dis-tribution are modelled following a nonparametric approach for the random-effects at regional level. This multilevel extension leads to the identification of a typology of regions, underlying a different social exclusion structure for different European areas. The model allows showing the relevance of the different dimensions and risk factors of social exclusion across regions, verifying whether and to what extent the same risks and disadvantages determine the same perception of marginalization and exclusion in different political, economic, social and cultural contexts. The analysis is carried out using the 56.1-2001 Eurobarometer Survey, which focused on poverty and social exclusion situations, from both a subjective and an objective point of view.
Published as Quality and Quantity, forthcoming.
Things Change: Women’s and Men’s Marital Disruption Dynamics in Italy during a Time of Social Transformation, 1970–2003
Silvana Salvini, Daniele Vignoli
Separations and divorces are on the rise in Italy. Are there trendsetters, i.e., forerunners of the new trend? Who are they? By applying an event-history analysis to the 2003 Italian Multipurpose Survey (“Families and Social Subjects”: the Italian variant of the Generations and Gender Survey), we found that the spread of a more flexible typology of unions started among women belonging to the middle-high social hierarchy. On the one hand, a remarkable composition effect emerges: in the 1990s, women’s educational shift (towards higher school completion levels) significantly contributed to the spread of the phenomenon. Beside, our findings evidence that a convergence process in the level of dissolution risk among various social strata is underway: namely, in recent decades, also women belonging to the lower social strata seem to be able to dissolve their unhappy unions. On the other hand, the trend in men’s marital disruption risk appears as a change over time common to all educational groups.
Published as Demographic Research, Volume 145-174, Issue 1, pp. 145-174, 2011; link, published.
wp2009_12 (Demography, Social Statistics)
Methods for “Reconciling” Micro and Macro in Family Demography Research: A Systematisation
Anna Matysiak, Daniele Vignoli
After mid-20th century the scientific study of population changed its paradigm from macro to micro so that the main focus of attention has been devoted to individuals as the agents of demographic action. However, to handle all the complexities of human behaviours, the interactions between individuals and the context they belong to cannot be ignored. Therefore, in order to explain (or, at least, understand) contemporary fertility and family dynamics the gap between micro and macro should be bridged. In this contribution we highlight two possible directions for bridging the gap: (1) integrating life-course analyses with contextual characteristics, thanks to the emergence of theory and tools of multi-level modelling and (2) bringing the findings at the micro-level back to macro-outcomes via meta-analytic techniques and agent-based computational models.
Published as Studia Demograficzne, Volume 155, Issue 1, pp. 98-109, 2010, published.
Evaluation of indirect identification systems based on STR DNA Profiles
In this paper we describe an approach to assess the potentiality of a probabilistic system for indirect identification through DNA evidence. The aim is, before an identification is attempted, to provide, the expected performances of the system and help all the parts involved to judge if the system fits their requirements. The analysis provided considers the probabilities associated to the weight of evidence related to the case, also suggesting possible strategies to improve the system. A detailed case study is illustrated as well as some possible information theoretic measures able to summarize the information capabilities of the DNA marker employed in a specific indirect identification.
Ultimo aggiornamento 10 aprile 2013.