Objective methods for graphical structural learning

Graphical models are used for expressing conditional independence relationships among variables by the means of graphs, whose structure is typically unknown and must be inferred by the data at hand. We propose a theoretically sound Objective Bayes procedure for graphical model selection. Our method is based on the Expected-Posterior Prior and on the Power-Expected-Posterior Prior. We use as input of the proposed methodology a default improper prior and suggest computationally efficient approximations of Bayes factors and posterior odds. In a variety of simulated scenarios with varying number of nodes and sample sizes, we show that our method is highly competitive with, or better than, current benchmarks. We also discuss an application to protein-signaling data, which wieldy confirms existing results in the scientific literature.     

Paired comparison models with age effects modeled as piecewise quadratic splines

We propose new models for analyzing pairwise comparison data, such as that relating to sports. We focus on changes in players’ strengths and the prediction of future results. Our models are based on the Thurstone-Mosteller and Bradley–Terry models, and make use of the time variation in the parameters. Furthermore, we apply our models to data from the Japanese traditional sport sumo, and analyze this data. The proposed models perform better than the standard Thurstone-Mosteller and Bradley–Terry models according to both the Akaike information criterion and the Brier score. We compare the proposed models in detail by focusing on individual sumo wrestlers.     

Service-Oriented Computing for intelligent train maintenance

The purpose of this work is to apply the servicization of enterprise information systems in maintenance, particularly in the management of the maintenance process of the component parts of trains. Service Oriented Architecture (SOA) is an architectural approach that permits servicization since it provides a flexible set of design principles used during the modeling practices (abstraction and realization). With a view to supporting the model-driven engineering of software systems, Mode Driven Architecture (MDA) is a design approach delivering a set of guidelines for the configuring of specifications in systems development. Therefore, the combination of these two approaches can be fruitful to address the challenging issues the enterprise information system is facing today. Our study is based on a methodological approach using the MDA models for the automatic generation of web service. The case study concerns a Railways Maintenance Workshop (RMW) at Sidi Bel Abbes (Algeria). Finally, the information system for the management of maintenance of the component parts of passengers and baggage railcars, using the generated solution, is realized and deployed. This software helps to have better management of the RMW by the effective planning of interventions, improve performance by increasing reliability, traceability, and availability of the equipment (parts).     

Pairs trading strategies in a cointegration framework: back-tested on CFD and optimized by profit factor

Statistical arbitrage is based on pairs trading of mean-reverting returns. We used cointegration approach and ECM-DCC-GARCH to construct 98 pairs of 152 stocks of 3 currencies. Stocks trading is done by Contract for Difference (CFD), a financial derivative product which facilitates short selling and provides a leverage up to 25 times. To measure the performance of a leveraged strategy, we introduced the profit factor which is the annualized return rate per unit risk. And the historical risk is measured by maximum drawdown. We compared three main strategies: percentage, standard deviation of cointegration long-term residuals and Bollinger Bands (dynamic standard deviation), with and without double confirmation of short-term standard deviation modelled by ECM-DCC-GARCH. Each of the three main strategies is optimized by two optimizers: absolute profit and profit factor. The optimization period goes from 2012–01-01 to 2014–12-31, and validation period is from 2015–01-01 to 2016–06-01. Our results showed that the USD Bollinger Bands strategy without double confirmation and optimized by profit factor, outperformed other strategies and provided the highest annualized return rate per unit risk; 32% of our sample pairs ended up in loss, and 94% of which are explained by a cointegration break during the testing period.     

Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model Averaging

In this paper we analyse the determinants of Japanese outward FDI stock for the period 1996–2017. This period is especially relevant as it covers a process of increasing economic globalization and two financial crises. To this aim, we consider a large set of candidate variables based on the theory as well as on previous empirical analysis. Our sample includes a total of 27 host countries. We select the covariates using a data-driven methodology, the Bayesian Model Averaging (BMA) analysis. Moreover, we also analyse whether these determinants change depending on the degree of development (emerging vs developed) or the geographical areas (EU vs East Asia) of the countries considered. We find that Japan's FDI can be explained by a wide variety of variables, that include not only the typical gravitational ones but also institutional and macroeconomic variables, including those that measure financial development. Moreover, Japanese FDI can be explained by both horizontal and vertical FDI motives in the groups of countries analysed. However, in developed, and more precisely, EU countries, horizontal FDI strategies are predominant, whereas for East Asian and emerging countries, there is more evidence in favour of vertical FDI.     

创业企业何以提高创新绩效——基于创业学习与商业模式创新协同联动视角的QCA方法

以150个创业企业为样本，基于创业学习和商业模式创新理论，运用模糊集定性比较分析方法（fsQCA），探究经验学习、认知学习、新颖型商业模式创新和效率型商业模式创新对创新绩效的影响路径及机制。研究发现，存在新颖型商业模式创新等4条创新绩效产出关键路径；相较于效率型商业模式创新，新颖型商业模式创新在关键路径中更容易提高创新绩效；利用QCA方法证实了影响创业企业创新绩效的组态内部各要素之间的替代性。结论丰富了创新绩效产出内部机制，可为创业企业提高创新绩效提供指导和借鉴。     

锚企业与科技新城共生模式研究:以阿里巴巴和杭州未来科技城为例

以阿里巴巴和杭州未来科技城为例，采用Logistic模型探讨锚企业与科技新城共生模式，结果表明：总体而言，阿里巴巴和未来科技城属于互利共生模式，阿里巴巴成长会促进未来科技城发展，而未来科技城发展也会反哺阿里巴巴的成长。2013-2016年两者共生系数之间的差值不断缩小，表明阿里巴巴和杭州未来科技城的共生模式从偏利共生转向互利共生。     

Correction to: Optimal and robust combination of forecasts via constrained optimization and shrinkage

We provide a correction to Proposition 1 in Optimal and robust combination of forecasts via constrained optimization and shrinkage, published in the International Journal of Forecasting 38(1):97-116 (2021). This correction has no impact on any other result (neither theoretical nor empirical) provided in the above paper.     

Information Contents in Japanese OTC Drug Advertising from Elaboration Likelihood Model Perspective: Content Analysis of TV Commercials and OTC Drug Websites

Based on the Elaboration Likelihood Model, the current study investigates information types that are cross-promoted in Japanese pharmaceutical advertising. The results from a quantitative content analysis of OTC drug brands' TV commercials broadcasted in Japan between 2014 and 2015 and their corresponding product websites (n = 150) show that Japanese OTC drug promotions feature more informational cues in the latter; cues such as price, safety, quality, components, and guarantees/warranties are particularly prominent. Furthermore, product websites tend to focus more on rational appeals, whereas TV commercials emphasize emotional appeals. No difference is found between these media types regarding celebrity and noncelebrity endorser usage.