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.     

考虑换乘费用的城市公共交通票价优化

换乘所产生的附加费用,如时间和票价等,导致配流影响因素产生变化,如果沿用传统方式将降低预测精度和可靠性。通过引入换乘次数和方式等因子计算出行等待、乘车、换乘及风险评估预留时间等,定义广义出行费用与计算方法;建立双层规划模型求解最优票价,最后通过算例分析弹性出行需求、换乘费用、票价之间的关系。计算结果表明,换乘费用对出行需求的影响小于票价优化对出行需求的影响,优化票价随换乘费用增加而加速降低,为公共交通票价优化提供研究依据。     

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.     

城市近郊区农户土地投入行为绩效评价及障碍因子诊断 ——耕地多功能价值视角下的多群组对比分析

研究目的:基于耕地多功能价值的视角研究农户土地投入行为绩效并诊断其障碍因子,以探索当前形势下城市近郊区农户"既不愿意种地,又不愿意将土地流转"的深层原因.研究方法:在构建农户土地投入行为绩效分析框架的基础上,通过农村入户调查获得样本数据,采用熵权TOPSIS法和障碍度模型,对不同性别和年龄阶段农户的土地投入行为展开绩效分析.研究结果:总体上,城市近郊区农户的土地投入行为绩效水平为"良好";多群组对比分析显示,男性绩效水平高于女性,青壮年绩效水平高于老年;补贴标准偏低和职业认同感差是制约土地投入行为绩效的主要障碍因子,而满足就业和养老需求依然是耕地资源的核心价值功能.研究结论:耕地在农户认知层面发挥着"弱保障"功能,"存而不用"的保守心态在事实上导致家庭承包地处于闲置、撂荒状态,这便是当前形势下城市近郊区耕地资源低效利用的底层逻辑.     

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。     

基于CE模型的河南省耕地生态补偿额度研究

[目的]基于生态补偿利益主体的需求和支付意愿,充分考虑区域经济发展状态,测算具有弹性的生态补偿标准,确保生态补偿机制顺利运行。[方法]以河南省457份实地调查问卷为基础,采用选择实验法,建立由4个属性水平、7个选择集组成的生态价值属性集,测算受访对象生态补偿的支付意愿。[结果]城乡居民对于耕地资源景观与生态环境关注度最高,其次是耕地质量和耕地面积;农民和市民对于耕地生态价值属性满足的支付意愿存在显著差异性,农民支付意愿为2 060.55元/hm~2,市民支付意愿为3 396.15元/hm~2,两者相差近1 335.60元/hm~2,收入水平、环保意识是影响受访对象生态补偿支付意愿的最直接因素,但两者均认为耕地面积不变、耕地质量改善和耕地景观生态环境改善为最优选择。[结论]补偿额度应充分考虑相关利益主体的支付能力和意愿,将农民的支付意愿作为生态补偿下限,市民的支付意愿作为生态补偿上限,可建立具有一定弹性的生态补偿机制。     

Forecasting value at risk and expected shortfall with mixed data sampling

I propose applying the Mixed Data Sampling (MIDAS) framework to forecast Value at Risk (VaR) and Expected shortfall (ES). The new methods exploit the serial dependence on short-horizon returns to directly forecast the tail dynamics of the desired horizon. I perform a comprehensive comparison of out-of-sample VaR and ES forecasts with established models for a wide range of financial assets and backtests. The MIDAS-based models significantly outperform traditional GARCH-based forecasts and alternative conditional quantile specifications, especially in terms of multi-day forecast horizons. My analysis advocates models that feature asymmetric conditional quantiles and the use of the Asymmetric Laplace density to jointly estimate VaR and ES.