On conditional risk estimation considering model risk

Usually, parametric procedures used for conditional variance modelling are associated with model risk. Model risk may affect the volatility and conditional value at risk estimation process either due to estimation or misspecification risks. Hence, non-parametric artificial intelligence models can be considered as alternative models given that they do not rely on an explicit form of the volatility. In this paper, we consider the least-squares support vector regression (LS-SVR), weighted LS-SVR and Fixed size LS-SVR models in order to handle the problem of conditional risk estimation taking into account issues of model risk. A simulation study and a real application show the performance of proposed volatility and VaR models.     

Divorce Chinese Style

This study investigated divorce during China's social and economic transformation period from 1970 to 2012. Specifically, the study examined the trend development of divorce and demonstrated how marriage formation type and individual socioeconomic characteristics were associated with the likelihood of divorce across time. Event‐history analysis was applied to longitudinal data from the China Family Panel Studies (2010–2012 waves). The results showed a threefold increase in divorce from the pre‐1990s to the 1990s. Surprisingly, the trend shifted to a plateau toward the 2000s. When cohabitation was in its rapidly diffusing stage in the 1990s, individuals who cohabited prior to marriage had a substantially higher likelihood of divorce. As cohabitation became increasingly common in the 2000s, its effect on divorce weakened. The role of socioeconomic characteristics in divorce also varied across time. This study enriches the knowledge of family dynamics in contemporary Chinese society.     

Improved Approximation for Breakpoint Graph Decomposition and Sorting by Reversals

Sorting by Reversals (SBR) is one of the most widely studied models of genome rearrangements in computational molecular biology. At present, is the best known approximation ratio achievable in polynomial time for SBR. A very closely related problem, called Breakpoint Graph Decomposition (BGD), calls for a largest collection of edge disjoint cycles in a suitably-defined graph. It has been shown that for almost all instances SBR is equivalent to BGD, in the sense that any solution of the latter corresponds to a solution of the former having the same value. In this paper, we show how to improve the approximation ratio achievable in polynomial time for BGD, from the previously known to for any > 0. Combined with the results in (Caprara, Journal of Combinatorial Optimization, vol. 3, pp. 149–182, 1999b), this yields the same approximation guarantee for n! – O((n – 5)!) out of the n! instances of SBR on permutations with n elements. Our result uses the best known approximation algorithms for Stable Set on graphs with maximum degree 4 as well as for Set Packing where the maximum size of a set is 6. Any improvement in the ratio achieved by these approximation algorithms will yield an automatic improvement of our result.     

Environmental and socioeconomic determinants of neonatal mortality in a northern Italian city in the early nineteenth century

Population and Environment - The research explores the effects of the environment on neonatal mortality in the early nineteenth century, controlling for social and economic factors. Individual...     

Statistical inference concerning weighted Poisson rates under some natural order restrictions

A conditional Poisson model is proposed for situations where one wants to compare the rate parameters for several populations, adjusting for a 'size' parameter and the random e ects of the subjects. Sometimes the physical nature of the problem makes it logical to consider some order restrictions on the rate parameters. The rate parameters are estimated and tested for under such order restrictions. This investigation is motivated by a real-life example on butterfly behavior, and the estimation and tests of hypotheses are illustrated over this data set.     

Non-parametric Regression with Dependent Censored Data

Abstract.  Let ( X _i , Y _i ) ( i = 1 ,…, n ) be n replications of a random vector ( X , Y  ), where Y is supposed to be subject to random right censoring. The data ( X _i , Y _i ) are assumed to come from a stationary α -mixing process. We consider the problem of estimating the function m ( x ) = E ( φ ( Y ) |  X = x ), for some known transformation φ . This problem is approached in the following way: first, we introduce a transformed variable     , that is not subject to censoring and satisfies the relation     , and then we estimate m ( x ) by applying local linear regression techniques. As a by-product, we obtain a general result on the uniform rate of convergence of kernel type estimators of functionals of an unknown distribution function, under strong mixing assumptions.     

Quality of Fit Measures in the Framework of Quantile Regression

Abstract. In regression experiments, to learn about the strength of the relationship between a covariate vector and a dependent variable, we propose a ‘coefficient of determination’ based on the quantiles. Such a coefficient is a ‘local’ measure in the sense that the strength is measured at a prespecified quantile level. Once estimated, it can be used, for example, to measure the relative importance of a subset of covariates in the quantile regression context. Related to this coefficient, we also propose a new ‘local’ lack‐of‐fit measure of a given parametric model. We provide some asymptotic results of the proposed measures and carry out a Monte Carlo simulation study to illustrate their use and performance in practice.     

Summer temperature effects on deaths and hospital admissions among the elderly population in two Italian cities

In developed countries the effects of climate on health status are mainly due to temperature. Our analysis is aimed to deepen statistically the relationship between summer climate conditions and daily frequency of health episodes: deaths or hospital admissions. We expect to find a U-shaped relationship between temperature and frequencies of events occurring in summer regarding the elderly population resident in Milano and Brescia. We use as covariates hourly records of temperature recorded at observation sites located in Milano and Brescia. The analysis is performed using Generalized Additive Models (GAM), where the response variable is the daily number of events, which varies as a possibly non-linear function of meteorological variables measured on the same or previous day. We consider separate models for Milano and Brescia and then we compare temperature effects among the two towns and among different age classes. Moreover we consider separate models for all diagnosed events, for those due to respiratory disease and those due to circulatory pathologies. Model selection is a central problem, the basic methods used are the UBRE and GCV criteria but, instead of conditioning all final conclusions on the best model according to the chosen criterion, we investigated the effect of model selection by implementing a bootstrap procedure.     

EXTENDING THE BOUNDARIES OF OPERATIONS MANAGEMENT: AN INTERNATIONAL FIELD-STUDIES APPROACH INTEGRATING INFORMATION SYSTEMS

Continued globalization, extensive use of information technologies, increasing cross-functional dependencies, and new organizational forms are rapidly changing the learning context of operations management. This paper describes an example of a mba elective course that has been created to address and learn from these new realities. We have taken a process view of the global firm, focusing mainly on the new product/service development, order fulfillment, and supply chain/ after-sales service processes. We have designed our course to contain most of the traditional topics in operations management (om) with information systems (is) woven in to support the key business processes. Our underlying belief is that these two functional areas should be seen as a blend, a seamless merging of the two fields, to obtain a competitive advantage. Besides teaching om and is in this integrated manner, the course engages in face-to-face student consulting projects with multinational companies. This paper describes our rationale for the course design and how it has been implemented over the last 6 years-as well as our plans for the future.