Research on a stock-matching trading strategy based on bi-objective optimization

In recent years, with strict domestic financial supervision and other policy-oriented factors, some products are becoming increasingly restricted, including nonstandard products, bank-guaranteed wealth management products, and other products that can provide investors with a more stable income. Pairs trading, a type of stable strategy that has proved efficient in many financial markets worldwide, has become the focus of investors. Based on the traditional Gatev–Goetzmann–Rouwenhorst (GGR, Gatev et al., 2006) strategy, this paper proposes a stock-matching strategy based on bi-objective quadratic programming with quadratic constraints (BQQ) model. Under the condition of ensuring a long-term equilibrium between pairedstock prices, the volatility of stock spreads is increased as much as possible, improving the profitability of the strategy. To verify the effectiveness of the strategy, we use the natural logs of the daily stock market indices in Shanghai. The GGR model and the BQQ model proposed in this paper are back-tested and compared. The results show that the BQQ model can achieve a higher rate of returns.     

Using a Delphi approach to identify the most efficacious interventions to improve Indonesia’s forest and land governance

Improvements to forest and land governance are key to addressing deforestation and degradation of peatlands in Indonesia. While this is a priority area, the steps to achieving good forest and land governance have been under-researched. There is a need for better links between theoretically informed academic analysis and work in the field. This study drew together a panel of experts on forest and land governance using a Delphi method to discuss the underlying drivers of deforestation and peatland degradation, and correspondingly, to identify interventions to improve land and forest governance in Indonesia. Seventeen panelists with an average of more than 12 years’ experience reached agreement over four governance interventions: increasing the capacity of local communities to manage and monitor forests and natural resources (65% of panelist’s votes); identify strengths and weaknesses of community organisations and institutions, and develop strategies to improve their performance (65% of panelist’s votes); gazetting forests to clarify land boundaries and determine which areas should be village, community and state forest zone (59% of panelist’s votes); and, integrating participatory community maps into spatial plans to protect local communities and indigenous peoples’ development needs (53% of panelist’s votes). They also supported action research involving the government, private sector and communities, and political economy approaches to researching forest and land governance issues. Panelists indicated that community level approaches such as securing community forest tenure through clarifying land claims and integrating local land tenure into spatial planning had an important role in sustainable forest management.     

The effects of exchange rate pass-through and cost channel on price level: The case of fragile five countries

ABSTRACT

In this study, we investigated whether the exchange rate and the interest rate had an effect on the inflation rate in the fragile five countries between the years of 1996Q4 and 2015Q4. In this context, a model was created to estimate the effect of interest rate and exchange rate on the inflation rate. The methods used in the study take into account cross-section dependence and heterogeneity. As a result of the analysis, it was determined that there was an exchange-rate and interest-rate pass-through effect in the fragile five countries. Moreover, it was found out that the cost channel and price puzzle were effective in Indonesia and South Africa but were not effective in Turkey, Brasil and India.     

Intergenerational Earnings Inequality: New Evidence From Italy

Using an innovative dataset built by merging survey and administrative data, we provide new estimates of intergenerational earnings’ inequality between fathers and sons in Italy, extending previous evidence in several directions. We rely on the TSTSLS method to predict fathers’ earnings and compute intergenerational elasticities and imputed rank–rank slopes, trying to reduce estimation biases. Confirming previous evidence, we find that Italy is characterized by a high intergenerational inequality in cross-country comparison. Extending previous analyses, we show that the intergenerational association increases when sons at older ages and multi-annual averages of pseudo-fathers’ and sons’ earnings are considered. We also find that the intergenerational persistence differs across geographical macro-areas and is high also for daughters, especially when family earnings are considered. Furthermore, estimates where possible mediating factors of the parental influence are included among the covariates show that a high intergenerational association persists when sons’ education and occupation are controlled for.     

Application of evidential reasoning approach and OWA operator weights in road safety evaluation considering the best and worst practice frontiers

Data envelopment analysis (DEA) has recently become relatively popular with road safety experts. Therefore, various decision-making units (DMUs), such as EU countries, have been assessed in terms of road safety performance (RSP). However, the DEA has been criticized because it evaluates DMUs based only on the concept of self-assessment, and, therefore does not provide a unique ranking for DMUs. Therefore, cross efficiency method (CEM) was developed to overcome this shortcoming. Peer-evaluations in addition to self-evaluation have made the CEM to be recognized as an effective method for ranking DMUs. The traditional CEM is based only on the standard CCR (Charnes, Cooper and Rhodes) model, and it evaluates DMUs according to their position relative to the best practice frontier while neglecting the worst practice frontier. However, the DMUs can also be assessed based on their position relative to the worst practice frontier. In this regard, the present study aims to provide a double-frontier CEM for assessing RSP by taking into account the best and worst frontiers simultaneously. For this purpose, the cross efficiency and cross anti-efficiency matrices are generated.Even though a weighted average method (WAM) is most frequently used for cross efficiency aggregation, the decision maker's (DM) preference structure may not be reflected. For this reason, the present study mainly focuses on the evidential reasoning approach (ERA), as a nonlinear aggregation method, rather than the linear WAM. Equal weights are often used for cross efficiency aggregation; consequently, the effect of the DM's subjective judgments in obtaining the overall efficiency is ignored. In this respect, the minimax entropy approach (MEA) and the maximum disparity approach (MMDA) are applied for determining the ordered weighted averaging (OWA) operator weights for cross efficiency aggregation. The weighted cross efficiencies and cross anti-efficiencies are then aggregated using the ERA. Finally, the proposed method, called DF-CEM-ERA, is used to evaluate the RSP of EU countries as well as Serbian police departments (PDs).     

Structural breaks in the mean of dividend-price ratios: Implications of learning on stock return predictability

In their out-of-sample predictions of stock returns in the presence of structural breaks, Lettau and Van Nieuwerburgh (2008) implicitly assume that economic agents’ perception of the regime-specific mean for the dividend-price ratio is time-invariant within a regime. In this paper, we challenge this assumption and employ least squares learning with constant gain (or constant-gain learning) in estimating economic agents’ time-varying perception for the mean of dividend-price ratio. We obtain better out-of-sample predictions of stock returns than in Lettau and Van Nieuwerburgh (2008) for both the U.S. and Japanese stock markets. Our empirical results suggest that economic agents’ learning plays an important role in the dynamics of stock returns.     

丝绸之路河西走廊物流业效率演化分析

构建了分析河西走廊物流业效率演化的指标体系,基于2009-2017年河西走廊物流业统计数据,运用DEA-Malmquist指数法测算了各市物流业效率和技术进步率,采用Tobit回归模型分析了该地区物流业效率的影响因素,并从省内、省域间、各经济区域间三个方面进行了对比分析。实证分析表明,相较于全国各省市地区,河西走廊物流业整体水平较低,物流业效率和技术进步率的强正相关性普遍存在,其物流业发展对政策偏向具有较强的依赖性;同时,技术进步率低下和基础设施匮乏也是制约物流业发展的重要因素。基于此,从政策照顾与资金投入、科技进步与管理水平和市场运营与体系建设三个方面,为河西走廊物流业发展提出了建议与改善措施。     

敦煌种业财务绩效评价研究

选择以农业上市公司敦煌种业为研究对象,以企业2014—2019年的报表数据为基础,采用功效系数法并以国务院国资委所编写的《企业绩效评价标准值》中国有企业绩效评价体系作为参考,构建对农业企业的财务指标评价体系,对敦煌种业2014-2019年企业财务指标的表现进行纵向分析,选择同行业中营业收入水平较高的北大荒进行横向对比,通过对比发现敦煌种业的问题主要体现在盈利能力和资产质量方面,对此提出了改进措施及建议。     

针对车辆AEB系统失效和误作用场景的研究

本文基于预期功能安全,采用功能分解方法,总结出部分车辆自动紧急制动(AEB)系统失效和误作用场景,并从中选取典型场景作为测试场景,开展不同车型的实车道路试验,总结出AEB系统的缺陷与隐患分类。希望此类研究能为AEB系统失效和误作用测试标准的制定提供参考。     

基于数字图像处理技术的再生混凝土数值模拟

为了研究骨料形态对再生混凝土材料力学性能的影响,基于势能原理的基面力元法,利用图像处理技术和MATLAB软件,建立了再生混凝土真实骨料细观模型。应用FORTRAN分析软件对再生混凝土试件进行单轴拉伸试验的数值模拟,研究了真实骨料细观模型再生混凝土宏观应力-应变曲线变化规律和试件的破坏形态。结果显示,真实骨料模型得到的宏观应力-应变曲线和试验曲线吻合度较高,骨料形状对试件的破坏形态影响较小。模型可真实地模拟再生混凝土在单轴拉伸作用下的损伤破坏过程,准确地反映试件的实际骨料形态。